Triple
T20562890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1976–77 Montreal Canadiens |
E504888
|
entity |
| Predicate | goalDifferential |
P51308
|
FINISHED |
| Object | +216 |
—
|
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: +216 | Statement: [1976–77 Montreal Canadiens, goalDifferential, +216]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goalDifferential Context triple: [1976–77 Montreal Canadiens, goalDifferential, +216]
-
A.
leagueGoalDifference
chosen
Indicates the numerical difference between goals scored and goals conceded by an entity within a league competition.
-
B.
usesGoalDifferenceTiebreaker
Indicates that when entities are tied, their ranking or outcome is decided based on the difference between goals scored and goals conceded.
-
C.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
equalisingGoalTeam
Indicates that a team scores a goal which brings the score level with the opposing team.
-
E.
goalsConceded
Indicates the number of goals a team or player has allowed the opposing side to score.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a79f906c819081163de9649ccb17 |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.