Triple
T33091777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John from Cincinnati |
E846800
|
entity |
| Predicate | hasMysticalCharacter |
P22515
|
FINISHED |
| Object | John Monad |
—
|
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: John Monad | Statement: [John from Cincinnati, hasMysticalCharacter, John Monad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMysticalCharacter Context triple: [John from Cincinnati, hasMysticalCharacter, John Monad]
-
A.
hasEnigmaticCharacter
chosen
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
B.
hasMythicalFigure
Indicates that one entity is associated with, features, or includes a particular mythical or legendary figure.
-
C.
hasMonkCharacter
Indicates that an entity includes or features a character whose role or identity is that of a monk.
-
D.
hasMythicMotif
Indicates that one entity features, embodies, or is associated with a particular mythic motif found in the other entity.
-
E.
hasMermaidCharacter
Indicates that an entity includes, features, or is associated with a character who is a mermaid.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:26 a.m.