Triple
T20157281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEN/Edward Bunker Prize for Fiction |
E491604
|
entity |
| Predicate | namedForNotableFact |
P124100
|
FINISHED |
| Object | former convict |
—
|
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: former convict | Statement: [PEN/Edward Bunker Prize for Fiction, namedForNotableFact, former convict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForNotableFact Context triple: [PEN/Edward Bunker Prize for Fiction, namedForNotableFact, former convict]
-
A.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
-
C.
namedForNotabilityOfHonoree
chosen
Indicates that something is named in recognition of the honoree’s notable achievements, status, or significance.
-
D.
namedPersonNotableFor
Indicates that a person is especially known or recognized for a particular work, role, achievement, or characteristic.
-
E.
sonNotableFor
Indicates that a son is recognized or distinguished for a particular achievement, role, or characteristic.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e18a0c8190a2cc2b305da28047 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.