Triple
T27903579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telangana–Maharashtra border |
E705705
|
entity |
| Predicate | languageZoneOnTelanganaSide |
P29819
|
FINISHED |
| Object | Telugu-speaking region |
—
|
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: Telugu-speaking region | Statement: [Telangana–Maharashtra border, languageZoneOnTelanganaSide, Telugu-speaking region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageZoneOnTelanganaSide Context triple: [Telangana–Maharashtra border, languageZoneOnTelanganaSide, Telugu-speaking region]
-
A.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
-
B.
locationUnionTerritory
Indicates that a location is situated within, or is part of, a specific union territory.
-
C.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
D.
timeZoneSideIndia
Indicates that something is located on, associated with, or aligned to the India side of a time zone boundary or division.
-
E.
languagePolicyRegion
Indicates that a particular language policy applies within, or is associated with, a specific geographic or administrative region.
- 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_69ef96b490ac8190a412d04c5d009f3e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: April 27, 2026, 6:43 p.m.