Triple
T8625186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gentlemen of Fortune |
E204263
|
entity |
| Predicate | hasDoppelgangerTheme |
P84501
|
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: [Gentlemen of Fortune, hasDoppelgangerTheme, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoppelgangerTheme Context triple: [Gentlemen of Fortune, hasDoppelgangerTheme, true]
-
A.
hasTwinSistersTheme
Indicates that something features or centers around the theme of twin sisters and their relationship or experiences.
-
B.
hasMythicTheme
Indicates that something embodies, references, or is characterized by a mythic or mythological theme.
-
C.
hasMotiveTheme
Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
-
D.
hasNicknameTheme
Indicates that an entity’s nickname is based on or associated with a particular theme or motif.
-
E.
hasTympanumTheme
Indicates that a subject features a specific thematic or narrative motif depicted in its tympanum (the semi-circular or triangular decorative space above a doorway or entrance).
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:26 p.m.