Triple
T15903029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagaung |
E385635
|
entity |
| Predicate | dayCountDependsOn |
P120993
|
FINISHED |
| Object | lunar cycle |
—
|
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: lunar cycle | Statement: [Wagaung, dayCountDependsOn, lunar cycle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dayCountDependsOn Context triple: [Wagaung, dayCountDependsOn, lunar cycle]
-
A.
hasDayCount
Indicates that an entity is associated with a specific number of days, expressing the duration or count of days related to it.
-
B.
specialDaysCount
Indicates the number of special or designated days associated with an entity or time period.
-
C.
dayTypeVariation
Indicates a relationship where the type or classification of a day differs from a standard or reference day type (e.g., special, holiday, or exceptional schedule).
-
D.
hasDays
Indicates that an entity is associated with, spans, or occurs on specific days.
-
E.
dayType
Indicates the classification or category of a given day based on its characteristics or role (e.g., weekday, weekend, holiday).
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.