Triple
T38290756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denton County Commissioner |
E1022354
|
entity |
| Predicate | numberOfSeatsOnBody |
P63301
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Denton County Commissioner, numberOfSeatsOnBody, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSeatsOnBody Context triple: [Denton County Commissioner, numberOfSeatsOnBody, 4]
-
A.
definesNumberOfSeats
Indicates that an entity specifies or determines the total number of seats associated with another entity.
-
B.
seatCount
chosen
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
C.
seatInBody
Indicates that something is positioned or installed within the main body or chassis of an object or structure.
-
D.
assemblySeatCount
Indicates the number of seats an entity holds in a legislative assembly.
-
E.
seatOnBody
Indicates that one entity functions as a seat or seating surface that is physically attached or integrated to a body or body-like structure.
- 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_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.