Triple
T35617170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Houghton |
E1029204
|
entity |
| Predicate | scoredWinningGoalAgainst |
P2220
|
FINISHED |
| Object | England national football team |
—
|
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: England national football team | Statement: [Ray Houghton, scoredWinningGoalAgainst, England national football team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredWinningGoalAgainst Context triple: [Ray Houghton, scoredWinningGoalAgainst, England national football team]
-
A.
hasOppositionGoal
Indicates that one entity’s goal is in direct conflict with, or aims to prevent the achievement of, another entity’s goal.
-
B.
famousGoalAgainst
Indicates that one entity is widely recognized for scoring a notable or iconic goal against another entity.
-
C.
scoredGameWinningGoal
chosen
Indicates that an entity scored the decisive goal that determined the final victory in a game.
-
D.
scoredHatTrickAgainst
Indicates that one entity scored three goals in a single game against another entity.
-
E.
scoredGoalsInFinalOf
Indicates that one entity scored one or more goals in the final match of a specified competition 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.