Triple
T9909822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunil Chhetri |
E185110
|
entity |
| Predicate | isAmongTopScorers |
P91094
|
FINISHED |
| Object | men’s international football |
—
|
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: men’s international football | Statement: [Sunil Chhetri, isAmongTopScorers, men’s international football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAmongTopScorers Context triple: [Sunil Chhetri, isAmongTopScorers, men’s international football]
-
A.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
B.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
C.
topScorerGamesPlayed
Indicates the number of games played by the entity who is the top scorer in a given context or competition.
-
D.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
E.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb51184d08190a0350f2722110811 |
completed | April 2, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69cd1d8c584081908b73de75eb18e438 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:41 p.m.