Triple
T10531826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binoy |
E248460
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | Gora |
E49286
|
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: Gora | Statement: [Binoy, appearsIn, Gora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gora Context triple: [Binoy, appearsIn, Gora]
-
A.
Gora
Gora is a mountainous border region in the Balkans known for its distinct Gorani Slavic Muslim community and shared cultural traditions across Kosovo, Albania, and North Macedonia.
-
B.
Gora
chosen
Gora is a major Bengali novel by Rabindranath Tagore that explores themes of identity, nationalism, and religious and social reform in colonial India.
-
C.
Gora
Gora is the nickname of Gourmohan, likely used as a familiar or affectionate short form of his given name.
-
D.
Gora Krasnaya
Gora Krasnaya is the highest elevation on the Samland Peninsula in the Kaliningrad region of Russia.
-
E.
Zelengora Mountain
Zelengora Mountain is a scenic mountain range in southeastern Bosnia and Herzegovina, renowned for its pristine glacial lakes, rich biodiversity, and extensive hiking opportunities.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a17f23081909f3372e160e21670 |
completed | April 7, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b3d6f6c81908d8247da9d9caab2 |
completed | April 10, 2026, 9:27 p.m. |
Created at: April 6, 2026, 12:30 p.m.