Triple
T34112746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandro Mazzola |
E874880
|
entity |
| Predicate | numberOfLeagueGoalsForClub |
P205323
|
FINISHED |
| Object | Inter Milan: 116 (Serie A) |
—
|
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: Inter Milan: 116 (Serie A) | Statement: [Sandro Mazzola, numberOfLeagueGoalsForClub, Inter Milan: 116 (Serie A)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLeagueGoalsForClub Context triple: [Sandro Mazzola, numberOfLeagueGoalsForClub, Inter Milan: 116 (Serie A)]
-
A.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
B.
leagueGoalsForArsenal
Indicates the number of league goals scored by Arsenal.
-
C.
premierLeagueGoals
Indicates the number of goals an entity has scored in the Premier League.
-
D.
ChelseaGoals
Indicates that the event or record involves goals scored by the football club Chelsea.
-
E.
leagueGoalDifference
Indicates the numerical difference between goals scored and goals conceded by an entity within a league competition.
- F. None of above. chosen
Provenance (4 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:53 a.m.