Triple
T27741805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey politics |
E701873
|
entity |
| Predicate | hasUSHouseDistrictsCount |
P1679
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [New Jersey politics, hasUSHouseDistrictsCount, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUSHouseDistrictsCount Context triple: [New Jersey politics, hasUSHouseDistrictsCount, 12]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
C.
homeDistrictOf
Indicates that a particular district is the primary or official home district associated with a given person or organization.
-
D.
numberOfHousingUnits
Indicates the total count of distinct housing units associated with an entity or within a specified area.
-
E.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 4:11 p.m.