Triple
T11022606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stony River, Alaska |
E260526
|
entity |
| Predicate | airportCode |
P418
|
FINISHED |
| Object |
SRV
SRV is the IATA airport code for the small public airport serving the remote community of Stony River in Alaska, United States.
|
E900366
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SRV | Statement: [Stony River, Alaska, airportCode, SRV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SRV Context triple: [Stony River, Alaska, airportCode, SRV]
-
A.
SRF
SRF is a French filmmakers' association best known for organizing the Directors' Fortnight sidebar at the Cannes Film Festival and advocating for directors' artistic and professional interests.
-
B.
SRF
SRF is the German-language division of the Swiss Broadcasting Corporation, responsible for producing and broadcasting radio, television, and online content in German-speaking Switzerland.
-
C.
SRU
SRU (Search/Retrieve via URL) is a standard web-based search protocol that enables querying and retrieving information from remote databases using URLs and XML.
-
D.
SVC
SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
-
E.
SVC
SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SRV Triple: [Stony River, Alaska, airportCode, SRV]
Generated description
SRV is the IATA airport code for the small public airport serving the remote community of Stony River in Alaska, United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SRV Target entity description: SRV is the IATA airport code for the small public airport serving the remote community of Stony River in Alaska, United States.
-
A.
SRF
SRF is the German-language division of the Swiss Broadcasting Corporation, responsible for producing and broadcasting radio, television, and online content in German-speaking Switzerland.
-
B.
SRF
SRF is a French filmmakers' association best known for organizing the Directors' Fortnight sidebar at the Cannes Film Festival and advocating for directors' artistic and professional interests.
-
C.
SRU
SRU (Search/Retrieve via URL) is a standard web-based search protocol that enables querying and retrieving information from remote databases using URLs and XML.
-
D.
SVC
SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
-
E.
SVC
SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797bd88188190a644adc9283cabb8 |
completed | April 9, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e374f64b3c8190b0b55193f81d3bc5 |
completed | April 18, 2026, 12:11 p.m. |
| NEDg | Description generation | batch_69e37ab860f48190808ba0076cfa9c98 |
completed | April 18, 2026, 12:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3864dd0d48190b3fd81381f5d7418 |
completed | April 18, 2026, 1:25 p.m. |
Created at: April 8, 2026, 9:25 p.m.