Triple
T746960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 4 (LAX) |
E15362
|
entity |
| Predicate | hasBoardingGatesFor |
P18603
|
FINISHED |
| Object | narrow-body aircraft |
—
|
LITERAL 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: narrow-body aircraft | Statement: [Terminal 4 (LAX), hasBoardingGatesFor, narrow-body aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingGatesFor Context triple: [Terminal 4 (LAX), hasBoardingGatesFor, narrow-body aircraft]
-
A.
isPartOfAirportLayout
Indicates that something is a component or element within the overall physical or functional layout of an airport.
-
B.
belongsToAirport
Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
-
C.
hasFaregates
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
D.
airportRole
Indicates that an entity serves a specific functional role or capacity within the context of an airport.
-
E.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
- F. None of above. chosen
Provenance (4 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62ca1d081908e3191411f86498d |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ff10608190bfd60b4a1cb38f7d |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.