Triple
T19662595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Purvis |
E472117
|
entity |
| Predicate | audienceWithinFiction |
P99109
|
FINISHED |
| Object | regulars at the White Hart pub |
—
|
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: regulars at the White Hart pub | Statement: [Harry Purvis, audienceWithinFiction, regulars at the White Hart pub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceWithinFiction Context triple: [Harry Purvis, audienceWithinFiction, regulars at the White Hart pub]
-
A.
eraWithinFiction
Indicates that a time period or era exists inside the narrative world or timeline of a fictional work.
-
B.
languageWithinFiction
Indicates that a language is used or exists within the context of a fictional work or fictional universe.
-
C.
showWithinFiction
Indicates that one entity is depicted, referenced, or occurs as part of the fictional world or narrative context of another entity.
-
D.
audienceWithinStory
chosen
Indicates that an audience exists as an internal, in-story observer or listener within the narrative itself, rather than outside it.
-
E.
cultureInFiction
Indicates that a work of fiction features, represents, or is thematically centered on a particular culture.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6414b30fc81908e6594ba8f2d2942 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.