Triple
T6980184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Totti |
E161821
|
entity |
| Predicate | topScorerInCompetition |
P6605
|
FINISHED |
| Object | AS Roma all-time top scorer |
—
|
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: AS Roma all-time top scorer | Statement: [Francesco Totti, topScorerInCompetition, AS Roma all-time top scorer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topScorerInCompetition Context triple: [Francesco Totti, topScorerInCompetition, AS Roma all-time top scorer]
-
A.
topScorer
chosen
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
B.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
C.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
D.
topScorerTeam
Indicates that a given team is the one with the highest score (or total points) in a particular game, season, or competition.
-
E.
leagueLeader
Indicates that the subject entity is currently ranked first or holds the top position within a specified league or competitive grouping.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db6c1efc8190ab1575ae2ce726db |
completed | March 27, 2026, 7:33 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.