Triple
T38047372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2006 Canadian federal election |
E949652
|
entity |
| Predicate | thirdPartySeatCount |
P193979
|
FINISHED |
| Object | 29 |
—
|
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: 29 | Statement: [2006 Canadian federal election, thirdPartySeatCount, 29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdPartySeatCount Context triple: [2006 Canadian federal election, thirdPartySeatCount, 29]
-
A.
thirdPartySeats
Indicates that a third-party entity is allocated or occupies seats (e.g., in a venue, vehicle, or governing body) associated with another primary party or arrangement.
-
B.
thirdPlaceSeatCount
Indicates the number of seats allocated to the entity that finished in third place in a given ranking or competition.
-
C.
seatCount
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
D.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
E.
secondPartySeats
Indicates that a second party assigns or provides seating or seats to another entity.
- 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_69f76f000cf081908c11fb5443b392e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd5bf69acc819092a01e4259785dc3 |
completed | May 8, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69fd59b3f4ac8190a7f9dd3142da6e09 |
completed | May 8, 2026, 3:34 a.m. |
| PDg | Predicate description generation | batch_69fd5bf49288819098a12202411cba4f |
completed | May 8, 2026, 3:43 a.m. |
Created at: May 3, 2026, 4:20 p.m.