Triple
T36983159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California State Senate district (Los Angeles County-based) |
E914887
|
entity |
| Predicate | usesTopTwoPrimary |
P193026
|
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: [California State Senate district (Los Angeles County-based), usesTopTwoPrimary, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTopTwoPrimary Context triple: [California State Senate district (Los Angeles County-based), usesTopTwoPrimary, yes]
-
A.
isPrimary
Indicates that one entity holds the main, leading, or most important role or status in relation to another entity or within a given context.
-
B.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
C.
hasPrimarySee
Indicates that one entity is designated as the main or preferred "see" reference or cross-reference for another entity.
-
D.
isPrimarySetFor
Indicates that one entity is designated as the main or default set associated with another entity.
-
E.
isPrimarilyUsedAs
Indicates that one entity serves mainly or most commonly in the role, function, or purpose specified by the other entity.
- F. None of above. chosen
Provenance (4 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_69f76e8dd0408190b8b46da118ea5128 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
| PDg | Predicate description generation | batch_69fd35d029588190a525aa8a506e7708 |
completed | May 8, 2026, 1:01 a.m. |
Created at: May 3, 2026, 4:14 p.m.