Triple
T9031920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phom Naga |
E216391
|
entity |
| Predicate | stateLanguageContext |
P10892
|
FINISHED |
| Object | Nagaland official language is English |
—
|
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: Nagaland official language is English | Statement: [Phom Naga, stateLanguageContext, Nagaland official language is English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateLanguageContext Context triple: [Phom Naga, stateLanguageContext, Nagaland official language is English]
-
A.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
regionLanguage
chosen
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
languageStatusSource
Indicates the source or authority from which the information about a language’s status is derived.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
positionOnLanguage
Indicates the stance, opinion, or viewpoint that an entity holds regarding a particular language.
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6a9f2c7481909b4a272183f20585 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.