Triple
T24293722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Jinx |
E605893
|
entity |
| Predicate | hasLiteraryCharacterRole |
P15535
|
FINISHED |
| Object | Blackford Oakes, CIA agent |
—
|
NE NERFINISHED |
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: Blackford Oakes, CIA agent | Statement: [High Jinx, hasLiteraryCharacterRole, Blackford Oakes, CIA agent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiteraryCharacterRole Context triple: [High Jinx, hasLiteraryCharacterRole, Blackford Oakes, CIA agent]
-
A.
literaryRole
chosen
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
B.
hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
C.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
D.
literarySeriesCharacter
Indicates that a character appears in, is part of, or is associated with a particular literary series.
-
E.
notableWorkCharacter
Indicates that a character appears in, is associated with, or plays a role in a particular notable work.
- 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_69e29549335881909cbf27adcaba1cf0 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f2915870c8819089c14de19ba2a5c5 |
completed | April 29, 2026, 11:16 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 12:09 a.m.