Triple
T8550859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikram |
E202439
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Vikram |
unclear NED1
|
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: Vikram | Statement: [Vikram, name, Vikram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vikram Context triple: [Vikram, name, Vikram]
-
A.
Vikram
Vikram is a prominent Indian actor best known for his versatile and intense performances in Tamil-language films.
-
B.
Vikram
Vikram is the lunar lander of India’s Chandrayaan-3 mission, designed to achieve a soft landing on the Moon’s surface.
-
C.
Aditya
Aditya is a Hindu solar deity associated with the group of Vedic sun gods known as the Adityas.
-
D.
Ramachandra
Ramachandra, better known as Tatya Tope, was a prominent Indian general and key leader of the 1857 Indian Rebellion against British rule.
-
E.
Ramachandra
Ramachandra is a common Indian male given name of Sanskrit origin, often associated with the Hindu deity Lord Rama.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe75589d8819096177ddbd3dafcb6 |
completed | March 31, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6dc7f6fc8190addd5d2bbe1f4408 |
completed | April 2, 2026, 1:23 p.m. |
Created at: March 30, 2026, 6:19 p.m.