Triple
T8105998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EZE |
E189226
|
entity |
| Predicate | hasPassengerTerminal |
P1297
|
FINISHED |
| Object | Terminal C |
E189232
|
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 C | Statement: [EZE, hasPassengerTerminal, Terminal C]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal C Context triple: [EZE, hasPassengerTerminal, Terminal C]
-
A.
Terminal C
Terminal C is one of the main passenger terminals at Boston Logan International Airport, serving numerous domestic and some international flights with a variety of airlines and amenities.
-
B.
Terminal C
Terminal C is one of the passenger terminals at Dallas/Fort Worth International Airport, serving various domestic flights and airlines within the airport’s complex.
-
C.
Terminal C
Terminal C is one of the passenger terminals at John Wayne Airport in Orange County, California, serving commercial airline flights and airport services.
-
D.
Terminal C
chosen
Terminal C is one of the passenger terminals at Ministro Pistarini International Airport (Ezeiza), serving as a key facility for airline operations and traveler services.
-
E.
Terminal C
Terminal C is one of the passenger terminals at Hannover Airport in Germany, serving commercial air traffic with check-in, security, and boarding facilities.
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42f735c8819090d0d822644c0a51 |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc6422fb4c8190a5e7bedd323241d7 |
completed | April 1, 2026, 12:17 a.m. |
Created at: March 30, 2026, 5:31 p.m.