Triple
T31963979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tennessee House of Representatives District 70 |
E816123
|
entity |
| Predicate | numberOfChamberSeats |
P136429
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Tennessee House of Representatives District 70, numberOfChamberSeats, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChamberSeats Context triple: [Tennessee House of Representatives District 70, numberOfChamberSeats, 1]
-
A.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
-
B.
seatCount
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
C.
definesNumberOfSeats
Indicates that an entity specifies or determines the total number of seats associated with another entity.
-
D.
assemblySeatCount
chosen
Indicates the number of seats an entity holds in a legislative assembly.
-
E.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
- 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_69f348f5ae5481909da0247869f51955 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a016cc5abcc8190b64094c777b40f6f |
completed | May 11, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_6a016b997ecc8190818207c57b9cbf17 |
completed | May 11, 2026, 5:39 a.m. |
Created at: May 1, 2026, 12:09 a.m.