Triple
T11433365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flórián Albert |
E270942
|
entity |
| Predicate | numberOfClubGoals |
P9098
|
FINISHED |
| Object | 256 (league, Ferencvárosi TC) |
—
|
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: 256 (league, Ferencvárosi TC) | Statement: [Flórián Albert, numberOfClubGoals, 256 (league, Ferencvárosi TC)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfClubGoals Context triple: [Flórián Albert, numberOfClubGoals, 256 (league, Ferencvárosi TC)]
-
A.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
B.
leagueGoalsAgainst
Indicates the number of goals a team has conceded in league competition against its opponents.
-
C.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
-
D.
scoredGoalSeason
Indicates that an entity scored a goal during a specified season.
-
E.
topGoalScorerGoals
Indicates the number of goals scored by the top goal scorer in a given context or competition.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c485f481909dd3d9b0993f3faf |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.