Triple
T25752248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chofetz Chaim Yeshiva |
E648495
|
entity |
| Predicate | primaryTextFocus |
P66120
|
FINISHED |
| Object | Talmud Bavli |
—
|
NE NERFINISHED |
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: Talmud Bavli | Statement: [Chofetz Chaim Yeshiva, primaryTextFocus, Talmud Bavli]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTextFocus Context triple: [Chofetz Chaim Yeshiva, primaryTextFocus, Talmud Bavli]
-
A.
primaryTextualFocus
Indicates that one entity is the main subject or central topic emphasized within the text of another entity.
-
B.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
C.
primaryTextUsed
chosen
Indicates that a particular text is the main or principal textual content used in relation to another entity or resource.
-
D.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
E.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
- 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 22, 2026, 4:36 a.m.