Triple
T14062799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jhansi Rani Lakshmibai award (various) |
E338387
|
entity |
| Predicate | hasNameComponent |
P24447
|
FINISHED |
| Object | Rani |
E338385
|
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: Rani | Statement: [Jhansi Rani Lakshmibai award (various), hasNameComponent, Rani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rani Context triple: [Jhansi Rani Lakshmibai award (various), hasNameComponent, Rani]
-
A.
Rani
chosen
Rani is an honorific title used in South Asia for a queen or a female royal consort.
-
B.
Ratna
Ratna is an Indonesian-born dancer and model who became known internationally as the second wife of French photographer Henri Cartier-Bresson.
-
C.
Ratna
Ratna is the middle name of Amala Ratna Zandile Dlamin, better known as the American rapper and singer Doja Cat.
-
D.
the Rani
The Rani is a brilliant but ruthless renegade Time Lord and recurring villain in the Doctor Who universe, known for her coldly scientific experiments and amoral pursuit of knowledge.
-
E.
Rajasbai
Rajasbai was a queen consort of the Maratha Empire, known primarily as one of the wives of Chhatrapati Rajaram I.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568876308190840361dcaf10bd45 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdefcc5708190beacccaa978a4abd |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:21 p.m.