Triple
T3720610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | traditional Chinese calendar |
E81628
|
entity |
| Predicate | averageYearLength |
P9857
|
FINISHED |
| Object | about 354 days without leap month |
—
|
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: about 354 days without leap month | Statement: [traditional Chinese calendar, averageYearLength, about 354 days without leap month]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageYearLength Context triple: [traditional Chinese calendar, averageYearLength, about 354 days without leap month]
-
A.
hasAverageYearLength
chosen
Indicates that one entity has a specified average duration for its year (orbital period), typically measured over time.
-
B.
hasAverageMonthLength
Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
-
C.
averageYearError
Indicates the average deviation, in years, between predicted and actual temporal values across instances.
-
D.
eraLengthYears
Indicates the duration of an era measured in years.
-
E.
additionalDaysPerYear
Indicates the number of extra days added each year to a base or standard duration.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca9b5ca8819094299fffc02606ce |
completed | March 8, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.