Triple
T2342836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English First Division 1964–65 |
E45063
|
entity |
| Predicate | usesPointsForWin |
P24875
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [English First Division 1964–65, usesPointsForWin, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPointsForWin Context triple: [English First Division 1964–65, usesPointsForWin, 2]
-
A.
pointsForWin
chosen
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
B.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
C.
numberOfWinsRequired
Indicates the specific count of wins an entity must achieve to meet a defined goal, threshold, or condition.
-
D.
earnsMorePointsThan
Indicates that one entity receives a greater number of points than another entity in a given context or comparison.
-
E.
conditionOfVictory
Indicates the specific circumstances or criteria under which a participant is considered to have won.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.