Triple
T14614852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herb Pennock |
E343057
|
entity |
| Predicate | worldSeriesTitleCount |
P115054
|
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: [Herb Pennock, worldSeriesTitleCount, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldSeriesTitleCount Context triple: [Herb Pennock, worldSeriesTitleCount, 7]
-
A.
worldSeriesTitles
Indicates the number of World Series championship titles an entity (typically a baseball team) has won.
-
B.
worldSeriesTitlesThroughYear
Indicates the number of World Series titles an entity has won up to and including a specified year.
-
C.
numberOfWorldSeriesTitles
Indicates the count of World Series championship titles that an entity (typically a baseball team or player) has won.
-
D.
WorldSeriesTitleWith
Indicates a relationship where two or more entities share a World Series championship title together in the same year or on the same team.
-
E.
worldSeriesTitleYear
Indicates the year in which a particular World Series title was won.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:25 a.m.