Triple
T9506704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Viollet |
E229287
|
entity |
| Predicate | leagueGoalsForManchesterUnitedIn1959-60Season |
P9098
|
FINISHED |
| Object | 32 |
—
|
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: 32 | Statement: [Dennis Viollet, leagueGoalsForManchesterUnitedIn1959-60Season, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueGoalsForManchesterUnitedIn1959-60Season Context triple: [Dennis Viollet, leagueGoalsForManchesterUnitedIn1959-60Season, 32]
-
A.
numberOfEnglandGoals
Indicates the number of goals scored by the England team in a given match or context.
-
B.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
C.
scoredGoalSeason
Indicates that an entity scored a goal during a specified season.
-
D.
seasonGoalsRecordSeason
Indicates the specific season in which a particular season goals record was achieved or is valid.
-
E.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98543b1881908b537abdc1d2f9c0 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:57 p.m.