Triple
T20351929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abhijit |
E496032
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Abijeet |
—
|
NE NERFINISHED |
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: Abijeet | Statement: [Abhijit, hasVariantSpelling, Abijeet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abijeet Context triple: [Abhijit, hasVariantSpelling, Abijeet]
-
A.
Abhijit
chosen
Abhijit is a common Indian male given name of Sanskrit origin, often associated with success and victory.
-
B.
Amarjeet
Amarjeet is a Canadian politician best known as Amarjeet Sohi, who has served as mayor of Edmonton and as a federal cabinet minister.
-
C.
Abirbhab
Abirbhab is a notable film performance by legendary Bangladeshi actor Razzak, recognized as part of his influential body of work in Bengali cinema.
-
D.
Parthibo
Parthibo is a Bengali literary work by acclaimed author Shirshendu Mukhopadhyay, known for its distinctive storytelling and exploration of human relationships.
-
E.
Balotra
Balotra is a town in the Indian state of Rajasthan, known as a regional commercial center and textile hub within the Barmer district.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67850ace48190b19aff5780fef7e8 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:24 a.m.