Triple
T23196984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Non-Resident Indians |
E579894
|
entity |
| Predicate | languageUsedInLaw |
P34970
|
FINISHED |
| Object | nonResident |
—
|
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: nonResident | Statement: [Non-Resident Indians, languageUsedInLaw, nonResident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedInLaw Context triple: [Non-Resident Indians, languageUsedInLaw, nonResident]
-
A.
languageInLaw
Indicates that a specific language is used as the official or operative language within a particular law or legal document.
-
B.
languageOfLegalCode
Indicates that a specified language is the language in which a particular legal code or body of law is written or officially expressed.
-
C.
languageOfJurisdiction
chosen
Indicates the language officially used for legal and administrative purposes within a given jurisdiction.
-
D.
usedLegalSystemOf
Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
-
E.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fdc0b8081909242fdc5cb1da517 |
completed | April 29, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:06 p.m.