Triple
T2954455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Carolina General Assembly |
E79897
|
entity |
| Predicate | numberOfMembersInHouse |
P45157
|
FINISHED |
| Object | 120 |
—
|
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: 120 | Statement: [North Carolina General Assembly, numberOfMembersInHouse, 120]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersInHouse Context triple: [North Carolina General Assembly, numberOfMembersInHouse, 120]
-
A.
numberOfMembersUpperHouse
Indicates the total count of individuals serving as members in the upper house of a legislative body.
-
B.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
C.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
D.
numberOfHousesInParliament
Indicates the count of distinct legislative chambers that make up a country's parliament.
-
E.
numberOfBoardMembers
Indicates the total count of individuals who serve as members on a board.
- F. None of above. chosen
Provenance (4 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98ff874c81908077a90fdc5e8549 |
completed | March 8, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:57 p.m.