Triple
T14802229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooper Cronk |
E347935
|
entity |
| Predicate | hadPremiershipStrippedYear |
P115782
|
FINISHED |
| Object | 2007 |
—
|
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: 2007 | Statement: [Cooper Cronk, hadPremiershipStrippedYear, 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPremiershipStrippedYear Context triple: [Cooper Cronk, hadPremiershipStrippedYear, 2007]
-
A.
premiershipYearAsPlayer
Indicates the year in which an individual participated as a player on a team that won a premiership or championship title.
-
B.
secondPremiershipYear
Indicates the year in which an entity held or achieved its second term of premiership.
-
C.
notablePremiershipYears
Indicates the years during which an entity held a notable or distinguished premiership (term as prime minister or equivalent head of government).
-
D.
premiershipCount
Indicates the number of premiership titles or championships an entity has won.
-
E.
sackedInYear
Indicates that an entity (such as a person in a role) was dismissed or fired from their position in a specified year.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf30d044819082ac038e06481aab |
completed | April 14, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.