Triple
T7640657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea City of India |
E172995
|
entity |
| Predicate | refersTo |
P37
|
FINISHED |
| Object | Dibrugarh |
E32155
|
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: Dibrugarh | Statement: [Tea City of India, refersTo, Dibrugarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dibrugarh Context triple: [Tea City of India, refersTo, Dibrugarh]
-
A.
Dibrugarh
chosen
Dibrugarh is a prominent city in northeastern India known as a major commercial and industrial hub of Assam, especially for its tea industry and oil and natural gas sectors.
-
B.
Tezpur
Tezpur is a historic city in northeastern India known for its cultural heritage, archaeological sites, and scenic location on the banks of the Brahmaputra River.
-
C.
Tinsukia
Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
-
D.
Jorhat
Jorhat is a prominent city in northeastern India known as a cultural and educational hub and a key center of the tea industry in Assam.
-
E.
Dimapur
Dimapur is a major commercial and transportation hub in northeastern India, serving as the primary gateway to the state of Nagaland.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facd9dec8190ab3af9cdde9992e6 |
completed | March 27, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ca621ce1b881908ed8145e0088ea3f |
completed | March 30, 2026, 11:44 a.m. |
Created at: March 27, 2026, 3:57 p.m.