Triple
T7697520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Justice of the Peace Courts |
E174405
|
entity |
| Predicate | numberOfPrecincts |
P78343
|
FINISHED |
| Object | varies by county |
—
|
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: varies by county | Statement: [Texas Justice of the Peace Courts, numberOfPrecincts, varies by county]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrecincts Context triple: [Texas Justice of the Peace Courts, numberOfPrecincts, varies by county]
-
A.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
B.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
C.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an entity.
-
D.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
E.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given 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_69c6995a72cc8190998e56daa6f8e453 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c70165e78c8190bf6b3c34e243cb81 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c7040091608190a9e46ecfb2ff0bca |
completed | March 27, 2026, 10:26 p.m. |
Created at: March 27, 2026, 4:03 p.m.