Triple
T14348956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ordeal by Innocence |
E355800
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Roopesh Parekh
Roopesh Parekh is a television and film producer known for his work on the adaptation of Agatha Christie's "Ordeal by Innocence."
|
E1092806
|
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: Roopesh Parekh | Statement: [Ordeal by Innocence, producer, Roopesh Parekh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roopesh Parekh Context triple: [Ordeal by Innocence, producer, Roopesh Parekh]
-
A.
Deepak Parekh
Deepak Parekh is a prominent Indian banker and business leader, best known for his long tenure as chairman of Housing Development Finance Corporation (HDFC) and his influential role in shaping India’s financial sector.
-
B.
Rohit Ghai
Rohit Ghai is a technology executive best known for serving as the CEO of cybersecurity company RSA Security.
-
C.
Ravi Kapoor
Ravi Kapoor is a filmmaker and creative professional best known for creating the project "Six Degrees."
-
D.
Deepak Kapur
Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
-
E.
Utsav Parekh
Utsav Parekh is an Indian businessman and sports investor best known as a co-owner of the Indian Super League football club Atlético de Kolkata.
- 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: Roopesh Parekh Triple: [Ordeal by Innocence, producer, Roopesh Parekh]
Generated description
Roopesh Parekh is a television and film producer known for his work on the adaptation of Agatha Christie's "Ordeal by Innocence."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roopesh Parekh Target entity description: Roopesh Parekh is a television and film producer known for his work on the adaptation of Agatha Christie's "Ordeal by Innocence."
-
A.
Deepak Parekh
Deepak Parekh is a prominent Indian banker and business leader, best known for his long tenure as chairman of Housing Development Finance Corporation (HDFC) and his influential role in shaping India’s financial sector.
-
B.
Rohit Ghai
Rohit Ghai is a technology executive best known for serving as the CEO of cybersecurity company RSA Security.
-
C.
Ravi Kapoor
Ravi Kapoor is a filmmaker and creative professional best known for creating the project "Six Degrees."
-
D.
Deepak Kapur
Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
-
E.
Utsav Parekh
Utsav Parekh is an Indian businessman and sports investor best known as a co-owner of the Indian Super League football club Atlético de Kolkata.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e8d081c8190ac805726a3e98f4c |
completed | April 14, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46a12ad08190a2f0dc5890ed5ce9 |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd4768edc881909a0c586b6d9568a3 |
completed | May 8, 2026, 2:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd47eb7db08190a68f60b255073d8d |
completed | May 8, 2026, 2:18 a.m. |
Created at: April 10, 2026, 1:14 a.m.