Triple
T2375960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 3rd congressional district |
E46198
|
entity |
| Predicate | isNumberedDistrictOfState |
P13468
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Texas's 3rd congressional district, isNumberedDistrictOfState, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNumberedDistrictOfState Context triple: [Texas's 3rd congressional district, isNumberedDistrictOfState, 3]
-
A.
federalDistrictNumber
chosen
Indicates the specific numbered federal electoral or administrative district associated with an entity.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
governorateOrDistrict
Indicates that one administrative region is a governorate or district that encompasses, governs, or is otherwise the primary subnational division for another area or locality.
-
D.
regionNumber
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
-
E.
hasJudicialDistrict
Indicates that an entity falls within or is associated with a specific judicial district for legal or court-related purposes.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.