Triple
T582176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kislev |
E15081
|
entity |
| Predicate | lengthVariabilityReason |
P13845
|
FINISHED |
| Object | Hebrew calendar leap year rules |
—
|
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: Hebrew calendar leap year rules | Statement: [Kislev, lengthVariabilityReason, Hebrew calendar leap year rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthVariabilityReason Context triple: [Kislev, lengthVariabilityReason, Hebrew calendar leap year rules]
-
A.
usageVariesBy
Indicates that the way something is used differs depending on a specified factor, such as context, user, location, or conditions.
-
B.
hasVariability
chosen
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
C.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
D.
viewVariesAmong
Indicates that the way something is viewed, perceived, or interpreted differs across multiple entities or contexts.
-
E.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b85becc8190b4d98c00e5fa7c04 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c7f9008190bd8d05b4dc2a7c7f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.