Triple
T16103942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Tuesday, 2008 |
E390691
|
entity |
| Predicate | numberOfStatesHoldingContests |
P121941
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [Super Tuesday, 2008, numberOfStatesHoldingContests, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStatesHoldingContests Context triple: [Super Tuesday, 2008, numberOfStatesHoldingContests, 24]
-
A.
electionContests
Indicates that one election is in competition with, or formally challenges the outcome or validity of, another election.
-
B.
numberOfSeatsContested
Indicates the total count of seats in an election or contest that are being competed for or are up for selection.
-
C.
hasOfficeContested
Indicates that an individual has been a candidate for a particular public office in an election.
-
D.
alsoContestedIn
Indicates that the same issue, claim, or matter is being disputed or challenged in another context, case, or proceeding as well.
-
E.
wasContestedIn
Indicates that an event, position, or decision was the subject of competition, dispute, or challenge within a particular context or proceeding.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6a4b8881908e8dc186381196d8 |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e182804208819087f35307cd6e4103 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 5 a.m.