Triple
T5403427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York congressional districts |
E120833
|
entity |
| Predicate | numberOfDistrictsPost2010Census |
P1679
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [New York congressional districts, numberOfDistrictsPost2010Census, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDistrictsPost2010Census Context triple: [New York congressional districts, numberOfDistrictsPost2010Census, 27]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
C.
numberOfDistrictMembers
Indicates the relationship that specifies how many members are associated with a given district.
-
D.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
E.
countyAfter2020Reform
Indicates that an administrative county exists in its form or status as defined following the 2020 reform.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.