Triple
T25452677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1955 FA Cup Final |
E637828
|
entity |
| Predicate | goalScorerForManchesterCity |
P2695
|
FINISHED |
| Object | Bobby Johnstone |
—
|
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: Bobby Johnstone | Statement: [1955 FA Cup Final, goalScorerForManchesterCity, Bobby Johnstone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalScorerForManchesterCity Context triple: [1955 FA Cup Final, goalScorerForManchesterCity, Bobby Johnstone]
-
A.
goalsForManchesterCity
Indicates the number of goals that were scored for Manchester City.
-
B.
goalScorer
chosen
Indicates that the subject is the player who scored a particular goal in a game or match.
-
C.
ManchesterCityGoalkeeper
Indicates that the subject serves as a goalkeeper for the Manchester City football club.
-
D.
notableGoalScorer
Indicates that the subject is recognized for having scored a significant or noteworthy number of goals, typically in a sports context.
-
E.
finalGoalscorer
Indicates that an entity is the player who scored the last goal in a particular match or event.
- 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_69e75db7c5048190b8da9cd7eeedb610 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f70885cc81909f1574406d67c682 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 2:03 p.m.