Triple
T5619787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rangat Tehsil |
E147571
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object | Rangat |
E174963
|
NE 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: Rangat | Statement: [Rangat Tehsil, includes, Rangat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rangat Context triple: [Rangat Tehsil, includes, Rangat]
-
A.
Rangat
chosen
Rangat is a coastal town and administrative hub located on Middle Andaman Island in the Andaman and Nicobar Islands, India.
-
B.
Tayauh
Tayauh was a participant in the Tepanec War, a conflict among pre-Columbian Nahua city-states in central Mexico.
-
C.
Ronga
Ronga is a Bantu language spoken primarily in southern Mozambique, known for contributing vocabulary and structural features to African varieties of Portuguese.
-
D.
Tilantongo
Tilantongo was a prominent pre-Columbian Mixtec city-state in present-day Oaxaca, Mexico, known as a political and cultural hub of the Mixtec civilization.
-
E.
Napareuli
Napareuli is a Georgian wine appellation in the Kakheti region, known for producing high-quality wines, particularly from the Saperavi grape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00905d4588190bd967842bbcf2219 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c022108db8819098739510366adee1 |
completed | March 22, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d59317c8190a4a3b186a46a7249 |
completed | March 22, 2026, 8:13 p.m. |
Created at: March 22, 2026, 3:40 p.m.