Triple
T961361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maurice Richard |
E20742
|
entity |
| Predicate | firstToAchieve |
P21887
|
FINISHED |
| Object | 50 goals in 50 games in an NHL season |
—
|
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: 50 goals in 50 games in an NHL season | Statement: [Maurice Richard, firstToAchieve, 50 goals in 50 games in an NHL season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstToAchieve Context triple: [Maurice Richard, firstToAchieve, 50 goals in 50 games in an NHL season]
-
A.
firstRunningWinner
Indicates that the subject is the first entity to win among those participating in a running event or race.
-
B.
firstWinner
Indicates that the subject is the entity who achieved first place or victory in the referenced event or competition.
-
C.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
D.
firstWinnerYear
Indicates the year in which an entity first won a particular competition, award, or title.
-
E.
firstSuccessfulImpactBy
Indicates that one entity is the earliest or initial successful impactor upon another entity in a given context or sequence of events.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4144c208190980936347a95e233 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a2e23c8190b932fe88b02f995d |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.