Triple
T36819580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maharsha |
E909841
|
entity |
| Predicate | standardTextIn |
P193751
|
FINISHED |
| Object | yeshiva study |
—
|
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: yeshiva study | Statement: [Maharsha, standardTextIn, yeshiva study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardTextIn Context triple: [Maharsha, standardTextIn, yeshiva study]
-
A.
standardWithin
Indicates that one entity conforms to, or falls within the limits of, a specified standard defined by another entity.
-
B.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
C.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
-
D.
standardBody
Indicates that an entity conforms to a recognized or officially accepted body type, form, or physical specification.
-
E.
standardUse
Indicates that something is used in a typical, expected, or officially accepted manner for its intended purpose.
- 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_69f76e7dd13c81908c60b05adb49eeb5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fd509cdc5c8190a5f2c451bc0d0b25 |
completed | May 8, 2026, 2:55 a.m. |
Created at: May 3, 2026, 4:13 p.m.