Triple
T33074659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gherardini family |
E846324
|
entity |
| Predicate | hasGenderLine |
P192725
|
FINISHED |
| Object | agnatic line |
—
|
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: agnatic line | Statement: [Gherardini family, hasGenderLine, agnatic line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderLine Context triple: [Gherardini family, hasGenderLine, agnatic line]
-
A.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
B.
hasGenderInText
Indicates that a specified gender is explicitly mentioned or assigned to an entity within a given text.
-
C.
hasGenderFormat
Indicates that something is associated with or expressed in a particular gender-related format or representation.
-
D.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
-
E.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
- 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
| PDg | Predicate description generation | batch_69fd28379d2c8190903ba228ee1cc756 |
completed | May 8, 2026, 12:03 a.m. |
Created at: May 1, 2026, 1:25 a.m.