Triple
T24906687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1993 Canadian federal election |
E623727
|
entity |
| Predicate | secondPlaceSeatCount |
P29125
|
FINISHED |
| Object | 54 |
—
|
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: 54 | Statement: [1993 Canadian federal election, secondPlaceSeatCount, 54]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPlaceSeatCount Context triple: [1993 Canadian federal election, secondPlaceSeatCount, 54]
-
A.
thirdPlaceSeatCount
Indicates the number of seats allocated to the entity that finished in third place in a given ranking or competition.
-
B.
secondPartySeats
Indicates that a second party assigns or provides seating or seats to another entity.
-
C.
hasSecondSeat
Indicates that an entity possesses or includes a secondary seat in addition to a primary one.
-
D.
secondPlace
chosen
Indicates that an entity holds the position of runner-up or finishes in second place in a ranked ordering, competition, or comparison relative to others.
-
E.
fifthPlaceSeatCount
Indicates the number of seats allocated to the entity that finished in fifth place.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f63182f1408190bddc1214fcbd6145 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 18, 2026, 5:27 a.m.