Triple
T31349531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korazin |
E799547
|
entity |
| Predicate | materialOfSynagogue |
P176351
|
FINISHED |
| Object | basalt |
—
|
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: basalt | Statement: [Korazin, materialOfSynagogue, basalt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialOfSynagogue Context triple: [Korazin, materialOfSynagogue, basalt]
-
A.
mainSynagogue
Indicates that one entity serves as the primary or principal synagogue associated with another entity (such as a place, community, or organization).
-
B.
builtSynagogue
Indicates that one entity constructed or was responsible for the building of a synagogue for another entity or community.
-
C.
hasSynagogueType
Indicates the specific classification or type of synagogue associated with an entity.
-
D.
templeMaterial
Indicates that a temple is constructed from, or primarily composed of, a specified material.
-
E.
materialOfChapelRuins
Indicates that a specified material was used in the construction of the chapel whose remains or ruins are being described.
- 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6dfcafd0c81908d86662948c539d6 |
completed | May 3, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6df418f488190a5e7ff41f32dceda |
completed | May 3, 2026, 5:38 a.m. |
Created at: April 29, 2026, 9:17 p.m.