Triple
T7073242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahesh Babu |
E164750
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Ramesh Babu |
E606558
|
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: Ramesh Babu | Statement: [Mahesh Babu, sibling, Ramesh Babu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramesh Babu Context triple: [Mahesh Babu, sibling, Ramesh Babu]
-
A.
Ramu Yalamanchi
Ramu Yalamanchi is an entrepreneur best known as the founder of the early social networking site hi5.
-
B.
Sai Madhav Burra
Sai Madhav Burra is an Indian screenwriter and dialogue writer known for his work on major Telugu films, including the epic action drama "RRR."
-
C.
Janardhan Rao
Janardhan Rao was a son of the prominent Maratha Peshwa Baji Rao I, belonging to the influential Peshwa family of the Maratha Empire.
-
D.
Manohar Raju
Manohar Raju is an American attorney and criminal justice reform advocate who serves as the elected Public Defender of San Francisco.
-
E.
D. Suresh Babu
chosen
D. Suresh Babu is an Indian film producer and prominent figure in the Telugu cinema industry, known for heading Suresh Productions.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4cb76548190bd98876f8ba925b7 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8569fbf4081909897b0e5456cd66a |
completed | March 28, 2026, 10:30 p.m. |
Created at: March 27, 2026, 2:39 p.m.