Triple
T32370670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Jasper |
E827124
|
entity |
| Predicate | characterInNotableWorkDescribedAs |
P115276
|
FINISHED |
| Object | intense and disciplined wrestler |
—
|
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: intense and disciplined wrestler | Statement: [Frank Jasper, characterInNotableWorkDescribedAs, intense and disciplined wrestler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInNotableWorkDescribedAs Context triple: [Frank Jasper, characterInNotableWorkDescribedAs, intense and disciplined wrestler]
-
A.
characterInWorkDescribedAs
chosen
Indicates that a character is portrayed or described in a particular way within a specific work.
-
B.
notableWorkCharacter
Indicates that a character appears in, is associated with, or plays a role in a particular notable work.
-
C.
notableCharacterType
Indicates that an entity is a notable or prominent example of a specified character type or role.
-
D.
notableEmployeeInFiction
Indicates that a person is a particularly prominent or significant employee within a fictional work or universe.
-
E.
notableDepictionBy
Indicates that an entity is significantly portrayed or represented by a particular creator, work, or medium.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: May 1, 2026, 12:50 a.m.