Triple
T36272381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trixie |
E892708
|
entity |
| Predicate | hasOffbeatDetectiveStory |
P191045
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Trixie, hasOffbeatDetectiveStory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOffbeatDetectiveStory Context triple: [Trixie, hasOffbeatDetectiveStory, true]
-
A.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
B.
fictionalDetective
Indicates that the subject is a detective character who exists only in fiction rather than in real life.
-
C.
companionOfDetective
Indicates a relationship where one entity serves as the detective’s close associate or partner, typically accompanying and assisting them in their investigative work.
-
D.
hasNotableFable
Indicates that an entity is associated with a well-known or significant fable, either as its subject, source, or key element.
-
E.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
- F. None of above. chosen
Provenance (4 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: May 3, 2026, 4:09 p.m.