Triple
T9512961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandusky Amtrak station |
E229446
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
SKY
SKY is the Amtrak station code for Sandusky station in Sandusky, Ohio, used for passenger rail ticketing and scheduling.
|
E804090
|
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: SKY | Statement: [Sandusky Amtrak station, hasStationCode, SKY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SKY Context triple: [Sandusky Amtrak station, hasStationCode, SKY]
-
A.
SKY
SKY is the ICAO airline designator used to identify Skymark Airlines in international aviation operations.
-
B.
SKYMARK
SKYMARK is the airline callsign used by Skymark Airlines, a Japanese low-cost carrier based in Tokyo.
-
C.
Sky 360
Sky 360 is a revolving restaurant located atop the Calgary Tower, offering panoramic views of Calgary and its surroundings.
-
D.
Sky
Sky is a charming and supportive young man from the musical and film "Mamma Mia!", known for his relationship with Sophie Sheridan and their plans to build a life together.
-
E.
Sky
"Sky" is a popular track by American rapper Playboi Carti, known for its hypnotic production and viral presence within the cloud rap and trap scenes.
- 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: SKY Triple: [Sandusky Amtrak station, hasStationCode, SKY]
Generated description
SKY is the Amtrak station code for Sandusky station in Sandusky, Ohio, used for passenger rail ticketing and scheduling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SKY Target entity description: SKY is the Amtrak station code for Sandusky station in Sandusky, Ohio, used for passenger rail ticketing and scheduling.
-
A.
SKY
SKY is the ICAO airline designator used to identify Skymark Airlines in international aviation operations.
-
B.
SKYMARK
SKYMARK is the airline callsign used by Skymark Airlines, a Japanese low-cost carrier based in Tokyo.
-
C.
Sky 360
Sky 360 is a revolving restaurant located atop the Calgary Tower, offering panoramic views of Calgary and its surroundings.
-
D.
Sky
Sky is a charming and supportive young man from the musical and film "Mamma Mia!", known for his relationship with Sophie Sheridan and their plans to build a life together.
-
E.
Sky
"Sky" is a popular track by American rapper Playboi Carti, known for its hypnotic production and viral presence within the cloud rap and trap scenes.
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd986aa99c8190b2eaa7f9b111aa2e |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a3e93a481908569a4ec80c834ab |
completed | April 4, 2026, 4:20 p.m. |
| NEDg | Description generation | batch_69d13c88a8b881909b024cf99a6a2778 |
completed | April 4, 2026, 4:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d13cfaab2c8190a6cc0fefeac7cd45 |
completed | April 4, 2026, 4:31 p.m. |
Created at: March 30, 2026, 7:58 p.m.