Triple
T35122607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FA Cup 2001–02 |
E1014201
|
entity |
| Predicate | numberOfGoalsInFinalByChelsea |
P9098
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [FA Cup 2001–02, numberOfGoalsInFinalByChelsea, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsInFinalByChelsea Context triple: [FA Cup 2001–02, numberOfGoalsInFinalByChelsea, 0]
-
A.
chelseaGoalkeeperInFinal
Indicates that the subject served as the goalkeeper for Chelsea in the specified final match.
-
B.
scoredGoalsInFinalOf
Indicates that one entity scored one or more goals in the final match of a specified competition or event.
-
C.
numberOfEnglandGoals
Indicates the number of goals scored by the England team in a given match or context.
-
D.
FA CupFinalScore
Indicates the final match score in an FA Cup competition, specifying how many goals each team scored in the deciding game.
-
E.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.