Triple
T2230895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Norris Memorial Trophy |
E48760
|
entity |
| Predicate | Doug Harvey_numberOfWins |
P36393
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [James Norris Memorial Trophy, Doug Harvey_numberOfWins, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Doug Harvey_numberOfWins Context triple: [James Norris Memorial Trophy, Doug Harvey_numberOfWins, 7]
-
A.
headCoachWinningTeam
Indicates that the subject is the head coach of the team that won a particular game, match, or competition.
-
B.
wonAgainst
Indicates that one entity achieved victory over another in a competition, conflict, or contest.
-
C.
seasonRecordWins
Indicates the number of games a team has won during a specific season.
-
D.
mostOverallWinsRecord
Indicates that the subject holds the record for having the greatest total number of wins compared to all others in the relevant context.
-
E.
numberOfNHLWins
Indicates the total count of games a team or individual has won in the National Hockey League.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc06b7374819089fe643e12797bfd |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe4252688190944491a450383450 |
completed | March 7, 2026, 5:57 a.m. |
Created at: March 4, 2026, 7:47 p.m.