Triple
T19622186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Charles Hurst |
E471038
|
entity |
| Predicate | numberOfGoalsScoredInMatch |
P9098
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Geoffrey Charles Hurst, numberOfGoalsScoredInMatch, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGoalsScoredInMatch Context triple: [Geoffrey Charles Hurst, numberOfGoalsScoredInMatch, 3]
-
A.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
B.
scoredGoalsInFinalOf
Indicates that one entity scored one or more goals in the final match of a specified competition or event.
-
C.
scoredInMatch
Indicates that an entity (typically a player or team) scored during a particular match.
-
D.
hasOppositionGoal
Indicates that one entity’s goal is in direct conflict with, or aims to prevent the achievement of, another entity’s goal.
-
E.
penaltyShootoutScore
Indicates the number of goals each side scored during a penalty shootout used to decide a tied match.
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e7949081908a89414ef899fa20 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.