Triple
T570887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Hollywood |
E13659
|
entity |
| Predicate | LGBTQFriendly |
P15143
|
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: [West Hollywood, LGBTQFriendly, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LGBTQFriendly Context triple: [West Hollywood, LGBTQFriendly, yes]
-
A.
sexualOrientation
Indicates an entity’s enduring pattern of romantic or sexual attraction toward others, typically in terms of the genders or sexes to which it is attracted.
-
B.
attitudeTowardDiversity
chosen
Indicates a stance, feeling, or evaluation that an entity holds regarding diversity or diverse groups.
-
C.
primaryVenueFor
Indicates that one entity serves as the main or principal venue or location for events, activities, or operations associated with another entity.
-
D.
servesAsFocusCityFor
Indicates that a city functions as a primary or designated focus city for an airline, organization, or transportation network, typically hosting significant but not hub-level operations or activities.
-
E.
hasPositionOnHomosexuality
Indicates that an entity holds a specific stance, view, or policy regarding homosexuality.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b483ac08190b3be152a7cf42011 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c2caac819086ab316fa49d324c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.