Triple
T8678876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1917–18 NHL season |
E205982
|
entity |
| Predicate | mostGoalsInSingleGameNumber |
P80657
|
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: [1917–18 NHL season, mostGoalsInSingleGameNumber, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostGoalsInSingleGameNumber Context triple: [1917–18 NHL season, mostGoalsInSingleGameNumber, 7]
-
A.
hitsInSingleGameRecord
Indicates that an entity holds the record for the most hits achieved in a single game.
-
B.
mostTriesScoredByPlayer
Indicates that the referenced player holds the record for scoring the highest number of tries, typically within a specified competition, season, or context.
-
C.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
scored71PointsInSingleGame
Indicates that an entity achieved a total of 71 points in a single game.
-
E.
topGoalScorerGoals
chosen
Indicates the number of goals scored by the top goal scorer in a given context or competition.
- 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_69ca835379688190aa06b9d98e684d58 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae6d19c8190be003f7901c0468d |
completed | March 31, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69cc4567b5c881908d9ec5dcfc783fac |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:32 p.m.