Triple
T35096100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim Filipinos |
E1012870
|
entity |
| Predicate | havePersonalLawSystem |
P153468
|
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: [Muslim Filipinos, havePersonalLawSystem, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: havePersonalLawSystem Context triple: [Muslim Filipinos, havePersonalLawSystem, true]
-
A.
usedLegalSystemOf
Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
-
B.
countryOfLegalSystem
Indicates the relationship between a legal system and the country in which that legal system is officially established or applied.
-
C.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
-
D.
appliesPersonalStatusLawTo
chosen
Indicates that a particular personal status law (e.g., relating to family, marriage, or inheritance) is applied to a given person or group.
-
E.
hasExtendedLawSystem
Indicates that an entity possesses a comprehensive, detailed, and well-developed system of laws or legal regulations.
- 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_69f76dd432ec8190969bc32acfc152b1 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.