Triple
T28450316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constable Kevin Goody |
E716558
|
entity |
| Predicate | worksUnderInFiction |
P170998
|
FINISHED |
| Object | Inspector Raymond Fowler |
—
|
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: Inspector Raymond Fowler | Statement: [Constable Kevin Goody, worksUnderInFiction, Inspector Raymond Fowler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksUnderInFiction Context triple: [Constable Kevin Goody, worksUnderInFiction, Inspector Raymond Fowler]
-
A.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
B.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
C.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
D.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
E.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 28, 2026, 1:51 a.m.