Triple
T34666778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | מסכת מועד קטן |
E890278
|
entity |
| Predicate | hasTractateOrder |
P200306
|
FINISHED |
| Object | סדר מועד |
—
|
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: סדר מועד | Statement: [מסכת מועד קטן, hasTractateOrder, סדר מועד]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTractateOrder Context triple: [מסכת מועד קטן, hasTractateOrder, סדר מועד]
-
A.
numberOfTractates
Indicates the total count of tractates associated with a given entity or collection.
-
B.
containsTractate
Indicates that one entity includes or encompasses a specific tractate as part of its contents or structure.
-
C.
appearsInTractate
Indicates that one entity (such as a topic, law, or passage) is contained within or discussed in a particular tractate.
-
D.
hasVerseOrder
Indicates that one verse is ordered or sequenced in relation to another verse within a structured text.
-
E.
approximateNumberOfTractates
Indicates a relationship where an entity is associated with an estimated or non-exact count of tractates linked to it.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69ff7fc715208190a8e4e2cc5aa72d2c |
completed | May 9, 2026, 6:41 p.m. |
Created at: May 1, 2026, 2:05 a.m.