Triple
T14172259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aemilii Paulli |
E351236
|
entity |
| Predicate | genderOfMembers |
P113101
|
FINISHED |
| Object | primarily male officeholders |
—
|
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: primarily male officeholders | Statement: [Aemilii Paulli, genderOfMembers, primarily male officeholders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderOfMembers Context triple: [Aemilii Paulli, genderOfMembers, primarily male officeholders]
-
A.
genderOfResidents
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
B.
genderDepicted
Indicates that the relationship specifies the gender of the entity as it is represented or portrayed in some context.
-
C.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
D.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
E.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b5dcbc8190b0cfcce5e6c6d582 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:01 a.m.