Triple
T24028984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 Indian Premier League |
E595042
|
entity |
| Predicate | mostRunsFor |
P23686
|
FINISHED |
| Object | Mumbai Indians |
—
|
NE NERFINISHED |
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: Mumbai Indians | Statement: [2010 Indian Premier League, mostRunsFor, Mumbai Indians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostRunsFor Context triple: [2010 Indian Premier League, mostRunsFor, Mumbai Indians]
-
A.
mostRuns
chosen
Indicates that one entity has scored a greater number of runs than all comparable entities in a given context or set.
-
B.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence or context.
-
C.
runsTheLengthOf
Indicates that one entity extends continuously alongside or across the full distance of another entity.
-
D.
largestWin
Indicates the relationship where one entity achieves its greatest margin or most significant victory over another in a competitive context.
-
E.
careerRuns
Indicates the total number of runs a player has scored over the entire duration of their professional career.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d76e10fc8190afa60c618a4398ee |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:54 p.m.