Triple
T2088065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of the City of Los Angeles |
E32600
|
entity |
| Predicate | numberOfCouncilDistricts |
P1679
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Government of the City of Los Angeles, numberOfCouncilDistricts, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCouncilDistricts Context triple: [Government of the City of Los Angeles, numberOfCouncilDistricts, 15]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
-
C.
numberOfRegionalCouncils
Indicates the total count of regional councils associated with a given entity.
-
D.
hasCouncilDistrict
Indicates that an entity is located within or represented by a specific council district.
-
E.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba712388819091d68a4bb99f6b17 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.