Triple
T360956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T5 |
E7849
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Terminal 5 |
E1837
|
NE FINISHED |
How this triple was built (2 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: Terminal 5 | Statement: [T5, alsoKnownAs, Terminal 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 5 Context triple: [T5, alsoKnownAs, Terminal 5]
-
A.
Terminal 5
chosen
Terminal 5 is a major passenger terminal at John F. Kennedy International Airport in New York City, known for serving as the primary hub for JetBlue Airways.
-
B.
Terminal 5
Terminal 5 is one of the passenger terminals at Los Angeles International Airport, serving a mix of domestic and some international flights with various airlines and amenities.
-
C.
Terminal 5
Terminal 5 is one of the passenger terminals at José Martí International Airport in Havana, Cuba, serving specific airlines and routes.
-
D.
Terminal 3
Terminal 3 is the main international passenger terminal at José Martí International Airport in Havana, Cuba, handling most long-haul and major airline operations.
-
E.
Terminal 3
Terminal 3 is one of the passenger terminals at Los Angeles International Airport, serving as a hub for several domestic and international airline operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebce64c88190a0a8edcc7095f78b |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a405f2a8108190a5d0398b7735661e |
completed | March 1, 2026, 9:25 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.