Triple
T4664872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tatya Tope |
E102821
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ramachandra |
E108087
|
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: Ramachandra | Statement: [Tatya Tope, givenName, Ramachandra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramachandra Context triple: [Tatya Tope, givenName, Ramachandra]
-
A.
Ramachandra
chosen
Ramachandra, better known as Tatya Tope, was a prominent Indian general and key leader of the 1857 Indian Rebellion against British rule.
-
B.
Rama
Rama is a major Hindu deity and the virtuous prince-king of Ayodhya, revered as the seventh avatar of Vishnu and hero of the epic Ramayana.
-
C.
Rama
Rama is a small scenic village in Pakistan’s Gilgit-Baltistan region, known as a gateway to the lush Rama Meadows and views of Nanga Parbat.
-
D.
Vikram
Vikram is a prominent Indian actor best known for his versatile and intense performances in Tamil-language films.
-
E.
Vikram
Vikram is the lunar lander of India’s Chandrayaan-3 mission, designed to achieve a soft landing on the Moon’s surface.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd633aeba88190a8329ed022d685b6 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03803a948190b6dc2a03bb9cdc93 |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:15 p.m.