Triple
T6490929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcel Dionne |
E148033
|
entity |
| Predicate | rankAllTimePoints |
P69988
|
FINISHED |
| Object | top 10 in NHL history |
—
|
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: top 10 in NHL history | Statement: [Marcel Dionne, rankAllTimePoints, top 10 in NHL history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankAllTimePoints Context triple: [Marcel Dionne, rankAllTimePoints, top 10 in NHL history]
-
A.
rankingPoints
Indicates the number of points assigned to an entity based on its position or performance in a ranking or competition.
-
B.
positionInAllTimeScoring
chosen
Indicates the ranking or placement of an entity within an all-time scoring leaderboard or cumulative scoring list.
-
C.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
D.
peakRanking
Indicates the highest position or rank an entity has ever achieved within a specified ranking system or context.
-
E.
globalRanking
Indicates the position or status of an entity relative to all comparable entities worldwide according to some ranking criteria.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a9a8d8481908d88e5c9f0c773f7 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:53 p.m.