Triple
T3999662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 4 |
E87183
|
entity |
| Predicate | hasArrivals |
P38073
|
FINISHED |
| Object | international arrivals area |
—
|
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: international arrivals area | Statement: [Terminal 4, hasArrivals, international arrivals area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArrivals Context triple: [Terminal 4, hasArrivals, international arrivals area]
-
A.
hasArrivalArea
chosen
Indicates that an entity is associated with a specific area designated for arrivals, such as where incoming people or items first enter or are received.
-
B.
hasArrangement
Indicates that one entity possesses, follows, or is organized according to a particular configuration, setup, or ordering defined by another entity.
-
C.
hasArrangementFor
Indicates that one entity has an established plan, setup, or provision in place to accommodate, support, or serve another entity or purpose.
-
D.
hasReception
Indicates that an entity hosts, includes, or is associated with a reception event (such as a formal gathering or welcoming function).
-
E.
availableWith
Indicates that one entity can be obtained, accessed, or used in conjunction with another entity.
- F. None of above.
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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.