Triple
T11815313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 1 |
E280984
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
T1 International
T1 International is the international passenger terminal at an airport commonly referred to as Terminal 1.
|
E947636
|
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: T1 International | Statement: [Terminal 1, alsoKnownAs, T1 International]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T1 International Context triple: [Terminal 1, alsoKnownAs, T1 International]
-
A.
TIJ
TIJ is the IATA airport code for Tijuana International Airport in Tijuana, Mexico.
-
B.
T’ai Federation
The T’ai Federation was an autonomous Tai ethnic polity in northwestern Vietnam under French colonial rule that fielded forces alongside the French during the First Indochina War.
-
C.
Tiance
Tiance was one of the reign era names used by Wu Zetian, the only female emperor in Chinese history, during her rule in the Tang dynasty.
-
D.
Leaf International
Leaf International was a confectionery company known for producing candies and chewing gum before being acquired by Cloetta.
-
E.
Tustar
Tustar is an ancient city in southwestern Iran, historically significant as a center of early Islamic scholarship and Sufi tradition.
- 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: T1 International Triple: [Terminal 1, alsoKnownAs, T1 International]
Generated description
T1 International is the international passenger terminal at an airport commonly referred to as Terminal 1.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T1 International Target entity description: T1 International is the international passenger terminal at an airport commonly referred to as Terminal 1.
-
A.
TIJ
TIJ is the IATA airport code for Tijuana International Airport in Tijuana, Mexico.
-
B.
T’ai Federation
The T’ai Federation was an autonomous Tai ethnic polity in northwestern Vietnam under French colonial rule that fielded forces alongside the French during the First Indochina War.
-
C.
Tiance
Tiance was one of the reign era names used by Wu Zetian, the only female emperor in Chinese history, during her rule in the Tang dynasty.
-
D.
Leaf International
Leaf International was a confectionery company known for producing candies and chewing gum before being acquired by Cloetta.
-
E.
Tustar
Tustar is an ancient city in southwestern Iran, historically significant as a center of early Islamic scholarship and Sufi tradition.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5ccbbd481908c9013cb5a50c079 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131b62abc8190a02f584541baaee5 |
completed | April 28, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69f141b31c9081908f19ff870f5f3c33 |
completed | April 28, 2026, 11:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f14fdb39d48190828668fc535d7f6a |
completed | April 29, 2026, 12:24 a.m. |
Created at: April 8, 2026, 9:42 p.m.