Triple
T6638148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Bloomer |
E150509
|
entity |
| Predicate | leagueGoalsForClub |
P9098
|
FINISHED |
| Object | Derby County F.C. – over 290 league goals |
—
|
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: Derby County F.C. – over 290 league goals | Statement: [Steve Bloomer, leagueGoalsForClub, Derby County F.C. – over 290 league goals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueGoalsForClub Context triple: [Steve Bloomer, leagueGoalsForClub, Derby County F.C. – over 290 league goals]
-
A.
leagueGoalsAgainst
Indicates the number of goals a team has conceded in league competition against its opponents.
-
B.
yearsAsPlayerAtClub
Indicates the number of years a person spent playing for a particular club.
-
C.
seasonGoalsRecordSeason
Indicates the specific season in which a particular season goals record was achieved or is valid.
-
D.
leagueGoalDifference
Indicates the numerical difference between goals scored and goals conceded by an entity within a league competition.
-
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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 2 p.m.