Triple
T276489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fields Corner |
E5259
|
entity |
| Predicate | hasPassengerInformationSystems |
P3794
|
FINISHED |
| Object | electronic message boards |
—
|
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: electronic message boards | Statement: [Fields Corner, hasPassengerInformationSystems, electronic message boards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerInformationSystems Context triple: [Fields Corner, hasPassengerInformationSystems, electronic message boards]
-
A.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
B.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
hasCustomerInformationScreens
chosen
Indicates that an entity is equipped with screens or displays that present information specifically intended for customers.
-
E.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.