Triple
T255561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood/Western station |
E5429
|
entity |
| Predicate | hasEmergencyCallBoxes |
P5951
|
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: [Hollywood/Western station, hasEmergencyCallBoxes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyCallBoxes Context triple: [Hollywood/Western station, hasEmergencyCallBoxes, yes]
-
A.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
B.
hasEmergencyIntercoms
chosen
Indicates that an entity is equipped with emergency intercom devices available for use in urgent or crisis situations.
-
C.
hasHelipads
Indicates that an entity possesses one or more helipads available for helicopter landing and takeoff.
-
D.
hasCCTV
Indicates that one entity is equipped with or monitored by a CCTV (closed-circuit television) system installed or provided by another entity.
-
E.
hasHazardSignage
Indicates that appropriate warning or hazard signs are present to alert people to potential dangers associated with the 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5669008190978bbd7308be11f7 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.