Triple
T12583379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnson County Commissioners Court |
E300393
|
entity |
| Predicate | numberOfPrecinctsRepresented |
P78343
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Johnson County Commissioners Court, numberOfPrecinctsRepresented, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrecinctsRepresented Context triple: [Johnson County Commissioners Court, numberOfPrecinctsRepresented, 4]
-
A.
numberOfPrecincts
chosen
Indicates the total count of precincts associated with a given entity or jurisdiction.
-
B.
hasNumberedPrecinct
Indicates that an entity is associated with a specific precinct identified by a number.
-
C.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
D.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
E.
countyRepresented
Indicates that a person or representative serves as the official representative for a particular county in a governing or organizational context.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:03 p.m.