Triple
T12010724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al HaNissim |
E285896
|
entity |
| Predicate | recitationGenderPractice |
P70787
|
FINISHED |
| Object | recited by both men and women in most communities |
—
|
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: recited by both men and women in most communities | Statement: [Al HaNissim, recitationGenderPractice, recited by both men and women in most communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recitationGenderPractice Context triple: [Al HaNissim, recitationGenderPractice, recited by both men and women in most communities]
-
A.
genderPracticeVariesBy
chosen
Indicates that the way gender is expressed, understood, or practiced differs depending on the specific context, group, or setting involved.
-
B.
playsGender
Indicates that one entity performs or assumes a particular gender role or identity in a given context.
-
C.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
D.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
E.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.