Triple
T31562184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kemp Mill Synagogue |
E805296
|
entity |
| Predicate | hasGenderSeparation |
P49314
|
FINISHED |
| Object | mechitza |
—
|
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: mechitza | Statement: [Kemp Mill Synagogue, hasGenderSeparation, mechitza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderSeparation Context triple: [Kemp Mill Synagogue, hasGenderSeparation, mechitza]
-
A.
hasGenderDivisions
chosen
Indicates that something is organized, classified, or separated into groups based on gender.
-
B.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
C.
hasGenderConvention
Indicates that there is an established or customary way of assigning or expressing gender within a given context, system, or culture.
-
D.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
E.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
- 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_69f348d22e088190ad555d5bd42f9da0 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: April 30, 2026, 10:15 p.m.