Triple
T23880408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National League Gold Glove at third base |
E600183
|
entity |
| Predicate | mostAwardsLeader |
P11369
|
FINISHED |
| Object | Mike Schmidt |
—
|
NE NERFINISHED |
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: Mike Schmidt | Statement: [National League Gold Glove at third base, mostAwardsLeader, Mike Schmidt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostAwardsLeader Context triple: [National League Gold Glove at third base, mostAwardsLeader, Mike Schmidt]
-
A.
mostAwardsHolder
chosen
Indicates that the subject is the entity that holds the highest number of awards within a given group or context.
-
B.
mostNominationsRecipient
Indicates that the subject is the entity that has received the highest number of nominations within a given context or set.
-
C.
mostNominationsCount
Indicates the highest number of nominations that any entity in the relevant set has received.
-
D.
mostAwardsArtistCount
Indicates the number of artists who share the highest total count of awards within a given context.
-
E.
mostAwardsFilmCount
Indicates the total number of awards received by the film that holds the record for having the most awards.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cc05226c8190aa640b6a89cb3ed3 |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:24 p.m.