Triple
T29855917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Digaru Mishmi |
E758187
|
entity |
| Predicate | adjacentAreas |
P75455
|
FINISHED |
| Object | border regions of India and China |
—
|
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: border regions of India and China | Statement: [Digaru Mishmi, adjacentAreas, border regions of India and China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentAreas Context triple: [Digaru Mishmi, adjacentAreas, border regions of India and China]
-
A.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
B.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
C.
neighboringTo
chosen
Indicates that one entity is located directly adjacent or very close to another entity, sharing a common boundary or immediate vicinity.
-
D.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
E.
locatedInOrAdjacentTo
Indicates that one entity is either situated within the boundaries of another entity or directly next to it, sharing a common border or edge.
- 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_69f2245a82cc8190a387e7d0118d710b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 29, 2026, 5:46 p.m.