Triple
T7073245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahesh Babu |
E164750
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Gautam Krishna
Gautam Krishna is the son of prominent Telugu film actor Mahesh Babu and is known primarily as a celebrity child in the Indian entertainment industry.
|
E644723
|
NE FINISHED |
How this triple was built (4 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: Gautam Krishna | Statement: [Mahesh Babu, child, Gautam Krishna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gautam Krishna Context triple: [Mahesh Babu, child, Gautam Krishna]
-
A.
Rahul Banga
Rahul Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
-
B.
Chaitanya Mangala
Chaitanya Mangala is a devotional biographical text in Bengali that narrates the life, teachings, and divine pastimes of the Vaishnava saint Chaitanya Mahaprabhu.
-
C.
Karthik Bala
Karthik Bala is a video game developer and entrepreneur best known as the co-founder of the game studio Vicarious Visions.
-
D.
Vijay Kumar
Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
-
E.
Nikhilesh
Nikhilesh is the introspective, progressive zamindar whose emotional and ideological journey anchors Rabindranath Tagore’s novel "Ghare-Baire" ("The Home and the World").
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gautam Krishna Triple: [Mahesh Babu, child, Gautam Krishna]
Generated description
Gautam Krishna is the son of prominent Telugu film actor Mahesh Babu and is known primarily as a celebrity child in the Indian entertainment industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gautam Krishna Target entity description: Gautam Krishna is the son of prominent Telugu film actor Mahesh Babu and is known primarily as a celebrity child in the Indian entertainment industry.
-
A.
Rahul Banga
Rahul Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
-
B.
Chaitanya Mangala
Chaitanya Mangala is a devotional biographical text in Bengali that narrates the life, teachings, and divine pastimes of the Vaishnava saint Chaitanya Mahaprabhu.
-
C.
Karthik Bala
Karthik Bala is a video game developer and entrepreneur best known as the co-founder of the game studio Vicarious Visions.
-
D.
Vijay Kumar
Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
-
E.
Nikhilesh
Nikhilesh is the introspective, progressive zamindar whose emotional and ideological journey anchors Rabindranath Tagore’s novel "Ghare-Baire" ("The Home and the World").
- F. None of above. chosen
Provenance (5 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_69c7ad7ba0188190bb59a0f9584d1923 |
completed | March 28, 2026, 10:29 a.m. |
| NEDg | Description generation | batch_69c7adef5d1c8190aea798aa98527295 |
completed | March 28, 2026, 10:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ae599cc8819086eadb1f1c25587a |
completed | March 28, 2026, 10:32 a.m. |
Created at: March 27, 2026, 2:39 p.m.