Triple
T38675408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gräfin zu Waldeck |
E943724
|
entity |
| Predicate | femaleFormOf |
P78555
|
FINISHED |
| Object | Graf zu Waldeck |
—
|
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: Graf zu Waldeck | Statement: [Gräfin zu Waldeck, femaleFormOf, Graf zu Waldeck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleFormOf Context triple: [Gräfin zu Waldeck, femaleFormOf, Graf zu Waldeck]
-
A.
femaleSubject
Indicates that the subject in the relationship or action is female.
-
B.
femaleHas
Indicates that a specified entity is female or possesses a female gender attribute in relation to another entity or context.
-
C.
femaleMember
Indicates that one entity is a member of a group or organization and is identified as female.
-
D.
femaleCounterpartOf
Indicates that one entity is the female equivalent or corresponding counterpart of another entity within a given role, relationship, or category.
-
E.
hasFemaleFormOf
chosen
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.