Triple
T20320307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman taken in adultery |
E492190
|
entity |
| Predicate | hasOtherFigure |
P37076
|
FINISHED |
| Object | scribes |
—
|
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: scribes | Statement: [Woman taken in adultery, hasOtherFigure, scribes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOtherFigure Context triple: [Woman taken in adultery, hasOtherFigure, scribes]
-
A.
hasCentralFigure
Indicates that something features a primary or most important figure at its core or focus.
-
B.
hasIconographicFigure
chosen
Indicates that one entity includes, depicts, or is associated with a particular iconographic figure in its visual or symbolic representation.
-
C.
hasMythicalFigure
Indicates that one entity is associated with, features, or includes a particular mythical or legendary figure.
-
D.
hasKeyFigure
Indicates that an entity includes, involves, or is characterized by an important or central person relevant to it.
-
E.
featuresFigureOf
Indicates that one entity includes or presents another entity as a figure, illustration, or visual element.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778b8b648190b80badaf15be2599 |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e5762655ac8190a8cc48a29fa2c0c4 |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:20 a.m.