Triple
T15334552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Coffey |
E366627
|
entity |
| Predicate | careerPointsRankAmongDefencemen |
P84504
|
FINISHED |
| Object | among all-time NHL leaders |
—
|
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: among all-time NHL leaders | Statement: [Paul Coffey, careerPointsRankAmongDefencemen, among all-time NHL leaders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerPointsRankAmongDefencemen Context triple: [Paul Coffey, careerPointsRankAmongDefencemen, among all-time NHL leaders]
-
A.
positionInNHLHistory
chosen
Indicates the relative ranking or placement of an entity within the historical timeline or ordered list of the NHL.
-
B.
bestDefenceman
Indicates that the subject is recognized as the top-performing or most outstanding defenceman among a specified group or within a particular context.
-
C.
NHLRookieSeasonPoints
Indicates the total number of points a player scored during their rookie season in the NHL.
-
D.
hasNumberOfDefencemen
Indicates the relationship that specifies how many defencemen are associated with or assigned to a given entity.
-
E.
numberOfNHLSeasons
Indicates the total count of seasons an entity has participated in the National Hockey League (NHL).
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e03c5f081908e4d14dbdbc7f7a6 |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.