Triple
T640764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adar I |
E16733
|
entity |
| Predicate | containsFast |
P17616
|
FINISHED |
| Object | Ta’anit Esther in some traditions |
—
|
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: Ta’anit Esther in some traditions | Statement: [Adar I, containsFast, Ta’anit Esther in some traditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFast Context triple: [Adar I, containsFast, Ta’anit Esther in some traditions]
-
A.
containsMostOf
Indicates that one entity includes the majority (but not necessarily all) of the substance, elements, or components of another entity.
-
B.
containsPass
Indicates that one entity includes or holds a valid pass or authorization credential within it.
-
C.
containsText
Indicates that one entity includes the specified text string within its content.
-
D.
includesElement
Indicates that one collection, set, or structure contains a specified element as a member or component.
-
E.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f0189b08190a584b744f36fa761 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.