Triple
T22108742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krishna Sobti |
E546358
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Ai Ladki
"Ai Ladki" is a celebrated Hindi novel by Krishna Sobti that explores the intimate, emotionally charged relationship between a dying mother and her daughter.
|
E1518436
|
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: Ai Ladki | Statement: [Krishna Sobti, notableWork, Ai Ladki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ai Ladki Context triple: [Krishna Sobti, notableWork, Ai Ladki]
-
A.
Woh Ladki
"Woh Ladki" is a Hindi song from the acclaimed 2018 black comedy thriller film *Andhadhun*, known for its melodious composition and romantic feel.
-
B.
Woh Ladki Hai Kahan
"Woh Ladki Hai Kahan" is a popular romantic-comedy song from the Hindi film *Dil Chahta Hai*, known for its playful lyrics and imaginative, retro-styled picturization.
-
C.
Chhoti Bahen
Chhoti Bahen is a 1959 Hindi family drama film directed by L.V. Prasad, known for its emotional storyline and popular music.
-
D.
Jeena
Jeena is the central protagonist of the Indian television series "Good Vibes."
-
E.
Ishka
Ishka is a Ferengi woman from Star Trek: Deep Space Nine, notable for being Quark and Rom’s progressive, profit-savvy mother who challenges traditional Ferengi gender norms.
- 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: Ai Ladki Triple: [Krishna Sobti, notableWork, Ai Ladki]
Generated description
"Ai Ladki" is a celebrated Hindi novel by Krishna Sobti that explores the intimate, emotionally charged relationship between a dying mother and her daughter.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ai Ladki Target entity description: "Ai Ladki" is a celebrated Hindi novel by Krishna Sobti that explores the intimate, emotionally charged relationship between a dying mother and her daughter.
-
A.
Woh Ladki
"Woh Ladki" is a Hindi song from the acclaimed 2018 black comedy thriller film *Andhadhun*, known for its melodious composition and romantic feel.
-
B.
Woh Ladki Hai Kahan
"Woh Ladki Hai Kahan" is a popular romantic-comedy song from the Hindi film *Dil Chahta Hai*, known for its playful lyrics and imaginative, retro-styled picturization.
-
C.
Chhoti Bahen
Chhoti Bahen is a 1959 Hindi family drama film directed by L.V. Prasad, known for its emotional storyline and popular music.
-
D.
Jeena
Jeena is the central protagonist of the Indian television series "Good Vibes."
-
E.
Ishka
Ishka is a Ferengi woman from Star Trek: Deep Space Nine, notable for being Quark and Rom’s progressive, profit-savvy mother who challenges traditional Ferengi gender norms.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291b9c988190b3ddd06d1f40dc78 |
completed | April 28, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a87ac12e881909ba2c0de6f3b26f5 |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a88e654ac8190a0e77e946bd9722b |
completed | May 18, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a8966298c8190a0d0e7d2b6eacdb4 |
completed | May 18, 2026, 3:37 a.m. |
Created at: April 16, 2026, 8:30 p.m.