Triple
T9196540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Erroll Garner Story |
E220727
|
entity |
| Predicate | hasBiographicalForm |
P60113
|
FINISHED |
| Object | chronicle |
—
|
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: chronicle | Statement: [The Erroll Garner Story, hasBiographicalForm, chronicle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBiographicalForm Context triple: [The Erroll Garner Story, hasBiographicalForm, chronicle]
-
A.
hasBiographicalTheme
Indicates that something (such as a work, text, or content) centers on or significantly involves biographical subject matter, such as a person’s life, experiences, or personal history.
-
B.
usesBiographicalStructure
chosen
Indicates that one entity employs or is organized according to the biographical structure of another entity (e.g., a work structured around a person’s life story).
-
C.
hasPartInBiography
Indicates that a person or entity is featured or plays a role within someone’s biographical account.
-
D.
includesBiographiesOf
Indicates that one entity contains or features biographical information about another entity.
-
E.
hasBiographicalSubjectOccupation
Indicates that the biographical subject is or was engaged in the specified occupation or profession.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd87d6460819097234b5dd3f749b4 |
completed | April 1, 2026, 8:34 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:25 p.m.