Triple
T17120092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iowa Republican caucuses, 2008 |
E415440
|
entity |
| Predicate | firstInNationContest |
P59622
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Iowa Republican caucuses, 2008, firstInNationContest, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstInNationContest Context triple: [Iowa Republican caucuses, 2008, firstInNationContest, true]
-
A.
wasFirstNationalContestAfter
Indicates that one national contest was the first such contest to occur after another specified national contest.
-
B.
firstForCountry
chosen
Indicates that the subject is the first instance or occurrence of its type to happen or exist within the specified country.
-
C.
firstRunningWinner
Indicates that the subject is the first entity to win among those participating in a running event or race.
-
D.
firstToAchieve
Indicates that one entity was the earliest or initial entity to accomplish or attain a specified goal, status, or outcome before any others.
-
E.
firstBroadcastInCountry
Indicates that a work (such as a program or broadcast) was first aired or transmitted in a specified country.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e8092b548190b45c1695be47edc2 |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:36 a.m.