Triple
T19669882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madhya Pradesh–Maharashtra border |
E472304
|
entity |
| Predicate | languageRegions |
P29819
|
FINISHED |
| Object | Hindi-speaking areas |
—
|
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: Hindi-speaking areas | Statement: [Madhya Pradesh–Maharashtra border, languageRegions, Hindi-speaking areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRegions Context triple: [Madhya Pradesh–Maharashtra border, languageRegions, Hindi-speaking areas]
-
A.
languageRegionsRepresented
Indicates that certain geographic or cultural regions are represented or covered through specific languages.
-
B.
languageFamilyRegion
Indicates the geographic region or area in which a language family is predominantly found or historically associated.
-
C.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
D.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
E.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416ad1b481908d2890d8c21aac5c |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.