Triple
T10888199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gita Bose |
E257105
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Gita Bose |
E257105
|
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: Gita Bose | Statement: [Gita Bose, name, Gita Bose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gita Bose Context triple: [Gita Bose, name, Gita Bose]
-
A.
Gita Bose
chosen
Gita Bose is a person notable for bearing the surname Bose, which is associated with several prominent figures in South Asian history and culture.
-
B.
Abala Bose
Abala Bose was an Indian social worker and feminist known for her pioneering efforts in women's education and welfare in colonial India.
-
C.
Kusumkumari Bose
Kusumkumari Bose was a Bengali poet and writer known for her contributions to early 20th-century Bengali literature.
-
D.
Sucheta Kriplani
Sucheta Kriplani was an Indian freedom fighter and politician who became the first woman Chief Minister of an Indian state, serving Uttar Pradesh.
-
E.
Premangshu Bose
Premangshu Bose is an actor known for his role in the Indian film "Nayak."
- 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75201e6888190a2bc41a17784eec3 |
completed | April 9, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e154f288b48190b0e840178d1071af |
completed | April 16, 2026, 9:30 p.m. |
Created at: April 8, 2026, 9:21 p.m.