Triple
T11023052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jody Baxter |
E260539
|
entity |
| Predicate | workReceivedAward |
P15639
|
FINISHED |
| Object | Pulitzer Prize for the novel’s author |
—
|
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: Pulitzer Prize for the novel’s author | Statement: [Jody Baxter, workReceivedAward, Pulitzer Prize for the novel’s author]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workReceivedAward Context triple: [Jody Baxter, workReceivedAward, Pulitzer Prize for the novel’s author]
-
A.
awardReceivedWith
Indicates that an entity received a specific award, optionally together with additional contextual details such as the work, role, or circumstances associated with that award.
-
B.
awardReceived
Indicates that an entity has been granted or honored with a specific award or recognition.
-
C.
awardReceivedByWork
chosen
Indicates that a particular award was given in recognition of a specific work (such as a book, film, or artwork).
-
D.
recipientOfAward
Indicates that an entity has received or been granted a particular award.
-
E.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797bd88188190a644adc9283cabb8 |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e995e008190bbffb314129ed0cd |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.