Triple
T36223189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FA WSL Golden Boot |
E1047910
|
entity |
| Predicate | goalsCounted |
P9098
|
FINISHED |
| Object | league matches only |
—
|
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: league matches only | Statement: [FA WSL Golden Boot, goalsCounted, league matches only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalsCounted Context triple: [FA WSL Golden Boot, goalsCounted, league matches only]
-
A.
goalNumber
Indicates that an entity is associated with a specific target or objective quantified as a number.
-
B.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
C.
goalsFor
Indicates the number of goals scored by one participant or team in favor of a particular side or match context.
-
D.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
E.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or 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_69f76e42c878819095c8d19c0267fb87 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b58275c08190a5ce7b3e575ddff7 |
completed | May 3, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.