Triple
T113511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebrew calendar |
E2294
|
entity |
| Predicate | hasVariableMonth |
P6445
|
FINISHED |
| Object | Kislev |
E15081
|
NE 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: Kislev | Statement: [Hebrew calendar, hasVariableMonth, Kislev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kislev Context triple: [Hebrew calendar, hasVariableMonth, Kislev]
-
A.
Kislev
chosen
Kislev is a late autumn/early winter month in the Hebrew calendar traditionally associated with the festival of Hanukkah.
-
B.
Tevet
Tevet is a winter month in the Hebrew calendar, typically falling in December–January and associated with several Jewish fasts and historical commemorations.
-
C.
Nisan
Nisan is the first month of the Hebrew religious year, traditionally associated with spring and the festival of Passover.
-
D.
Cheshvan
Cheshvan is the eighth month of the Hebrew calendar, traditionally noted for having no major Jewish holidays.
-
E.
Tammuz
Tammuz is the fourth month of the Hebrew religious calendar, traditionally falling in early summer and associated with historical fasts and mourning in Jewish tradition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25b800d08819099a44429d5c82c68 |
completed | Feb. 28, 2026, 3:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c938950081909990f481604ea022 |
completed | Feb. 28, 2026, 10:53 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.