Triple
T32965623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anton Koberger |
E843358
|
entity |
| Predicate | relationshipToAlbrechtDurer |
P137012
|
FINISHED |
| Object | godfather |
—
|
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: godfather | Statement: [Anton Koberger, relationshipToAlbrechtDurer, godfather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlbrechtDurer Context triple: [Anton Koberger, relationshipToAlbrechtDurer, godfather]
-
A.
relationshipToAlbrecht
chosen
Indicates a specified type of relational connection that an entity has to Albrecht.
-
B.
relationshipToGustav von Aschenbach
Indicates the specific type of personal, social, or emotional connection an entity has to Gustav von Aschenbach.
-
C.
relationshipToCharlesV
Indicates the specific familial or social relationship that one entity has to Charles V.
-
D.
possibleRelationshipToDiegoVelázquez
Indicates a potential or hypothesized relational connection (such as familial, professional, or social) that an entity may have to Diego Velázquez.
-
E.
relationshipTypeWithWilhelm Meister
Indicates the specific type or nature of the relationship that an entity has with Wilhelm Meister.
- 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_69f3494af2808190ad98cec2f1bc0fe6 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:21 a.m.