Triple
T9718710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamic holidays |
E235406
|
entity |
| Predicate | legalStatusVariesByCountry |
P39644
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Islamic holidays, legalStatusVariesByCountry, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusVariesByCountry Context triple: [Islamic holidays, legalStatusVariesByCountry, true]
-
A.
legalStatusVariesBy
chosen
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
B.
legalStatusInManyCountries
Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
-
C.
legalStatusAccordingToIndia
Indicates the legal status or classification of an entity as defined specifically by the laws and regulations of India.
-
D.
legalStatusInHomeland
Indicates the legal status or classification an entity holds within its country or place of origin.
-
E.
hasHighestLegalStatusWithinCountry
Indicates that an entity holds the topmost legally recognized status or rank within a specific country, above all other comparable statuses.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e3ea61081908a5671fc5be9a738 |
completed | April 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.