Triple
T1234588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal D |
E26517
|
entity |
| Predicate | hasInformationDesks |
P12416
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Terminal D, hasInformationDesks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInformationDesks Context triple: [Terminal D, hasInformationDesks, yes]
-
A.
hasInformationService
Indicates that one entity provides, operates, or is associated with an information-related service for another entity.
-
B.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
D.
providesInformationIn
Indicates that one entity supplies or conveys information within or through another entity or context.
-
E.
hasDiscoveryFacility
Indicates that an entity has, is associated with, or is served by a facility where discoveries (such as scientific, medical, or technological findings) are made or were made.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5e421081908f2432528019db25 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.