Triple
T509177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Bourque |
E10567
|
entity |
| Predicate | NorrisTrophyWins |
P14537
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Ray Bourque, NorrisTrophyWins, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NorrisTrophyWins Context triple: [Ray Bourque, NorrisTrophyWins, 5]
-
A.
norrisTrophyWinYear
Indicates the specific year in which an entity won the Norris Trophy.
-
B.
ConnSmytheTrophy
Indicates that an entity has been awarded the Conn Smythe Trophy, recognizing them as the most valuable player during the National Hockey League’s Stanley Cup playoffs.
-
C.
VezinaTrophyYear
Indicates the year in which a given Vezina Trophy was awarded or associated with a particular recipient.
-
D.
JamesNorrisMemorialTrophy
Indicates that an ice hockey player has been awarded the James Norris Memorial Trophy, recognizing them as the league’s top defenseman for that season.
-
E.
KingClancyTrophyYear
Indicates the year in which a given instance of the King Clancy Memorial Trophy was awarded.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f162f3888190b057ad04e40a30e2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.