Triple
T34183044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Crescenta |
E876875
|
entity |
| Predicate | countyServiceArea |
P165827
|
FINISHED |
| Object | Los Angeles County Fire Department |
—
|
NE NERFINISHED |
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: Los Angeles County Fire Department | Statement: [La Crescenta, countyServiceArea, Los Angeles County Fire Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyServiceArea Context triple: [La Crescenta, countyServiceArea, Los Angeles County Fire Department]
-
A.
areaOfService
Indicates the geographic or functional region within which a service is provided or applicable.
-
B.
serviceAreaName
Indicates the designated name of the geographic or functional area that a service covers or operates within.
-
C.
serviceAreaRelationship
chosen
Indicates a relationship in which one entity defines, covers, or is responsible for providing services within a specific geographic or functional area associated with another entity.
-
D.
countyRegion
Indicates that a county is located within, or is administratively part of, a larger geographic region.
-
E.
isInCountySeatAreaOfInfluence
Indicates that one location lies within the geographic or functional area of influence of a county seat.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a013632a3048190b05716d803f34716 |
completed | May 11, 2026, 1:51 a.m. |
| PD | Predicate disambiguation | batch_6a01309582e48190a05d47d96ffb7a46 |
completed | May 11, 2026, 1:27 a.m. |
Created at: May 1, 2026, 1:55 a.m.