Triple
T32474783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genealogy of Jesus |
E829941
|
entity |
| Predicate | includesWoman |
P203737
|
FINISHED |
| Object | Tamar |
E1212898
|
NE 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: Tamar | Statement: [Genealogy of Jesus, includesWoman, Tamar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesWoman Context triple: [Genealogy of Jesus, includesWoman, Tamar]
-
A.
includesWomenStructure
Indicates that the referenced entity contains or incorporates a structural component specifically designed for or involving women.
-
B.
womenSection
Indicates that something is designated as belonging to, located in, or associated with the women's section or area.
-
C.
includesBothGenders
Indicates that the referenced group, set, or category contains members of both male and female genders.
-
D.
femaleCounterpartOf
Indicates that one entity is the female equivalent or corresponding counterpart of another entity within a given role, relationship, or category.
-
E.
femaleMember
Indicates that one entity is a member of a group or organization and is identified as female.
- F. None of above. chosen
Provenance (5 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01d7b3ce8c8190b2f90be730505765 |
completed | May 11, 2026, 1:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34669baa448190b023d97bde0cee01 |
completed | June 18, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_6a01d5115a6c8190a6d9f96ec484135a |
completed | May 11, 2026, 1:09 p.m. |
| PDg | Predicate description generation | batch_6a01d7b312908190bae3320b9c206cae |
completed | May 11, 2026, 1:20 p.m. |
Created at: May 1, 2026, 12:58 a.m.