Triple
T14993664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 United States House of Representatives elections |
E373900
|
entity |
| Predicate | numberOfVotingDistricts |
P1679
|
FINISHED |
| Object | 435 |
—
|
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: 435 | Statement: [2018 United States House of Representatives elections, numberOfVotingDistricts, 435]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVotingDistricts Context triple: [2018 United States House of Representatives elections, numberOfVotingDistricts, 435]
-
A.
numberOfDistricts
chosen
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.
numberOfDistrictMembers
Indicates the relationship that specifies how many members are associated with a given district.
-
D.
numberOfPrecincts
Indicates the total count of precincts associated with a given entity or jurisdiction.
-
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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded716ebb481908224d2d4f7561b03 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:53 a.m.