Triple
T37150710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas (The Voyeurs) |
E920353
|
entity |
| Predicate | characterInPlotType |
P23263
|
FINISHED |
| Object | voyeurism-centered narrative |
—
|
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: voyeurism-centered narrative | Statement: [Thomas (The Voyeurs), characterInPlotType, voyeurism-centered narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInPlotType Context triple: [Thomas (The Voyeurs), characterInPlotType, voyeurism-centered narrative]
-
A.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
B.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
C.
characters
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
-
D.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
E.
storyCharacterizedAs
Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
- 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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4:15 p.m.