Triple
T113493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebrew calendar |
E2294
|
entity |
| Predicate | hasCommonYearMonthCount |
P6435
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Hebrew calendar, hasCommonYearMonthCount, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonYearMonthCount Context triple: [Hebrew calendar, hasCommonYearMonthCount, 12]
-
A.
hasCommonValue
Indicates that two or more entities share at least one identical value or attribute in common.
-
B.
monthObserved
Indicates the month during which an event, observation, or measurement took place.
-
C.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
-
D.
dateDetermination
Indicates the process or criteria by which a specific date is identified, calculated, or assigned in relation to an event or condition.
-
E.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.