Triple

T3820238
Position Surface form Disambiguated ID Type / Status
Subject Mars (TV series) E84352 entity
Predicate mainCastMember P5563 FINISHED
Object Akbar Kurtha
Akbar Kurtha is a British actor known for his roles in film and television, including a main cast role in the science fiction series "Mars."
E393308 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: Akbar Kurtha | Statement: [Mars (TV series), mainCastMember, Akbar Kurtha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akbar Kurtha
Context triple: [Mars (TV series), mainCastMember, Akbar Kurtha]
  • A. Jagat Singh
    Jagat Singh was a brother of Indian revolutionary Bhagat Singh, belonging to the same politically active Sandhu Jat Sikh family from Punjab.
  • B. Dinesh Chugtai
    Dinesh Chugtai is a socially awkward yet ambitious software engineer and programmer from the comedy TV series "Silicon Valley."
  • C. Gor Khatri
    Gor Khatri is a historic Mughal-era caravanserai and archaeological complex in Peshawar, Pakistan, known for its layers of ancient remains and religious significance over centuries.
  • D. Sher Afgan Khan
    Sher Afgan Khan was a Mughal nobleman and military officer best known as the first husband of the influential empress Nur Jahan.
  • E. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • 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: Akbar Kurtha
Triple: [Mars (TV series), mainCastMember, Akbar Kurtha]
Generated description
Akbar Kurtha is a British actor known for his roles in film and television, including a main cast role in the science fiction series "Mars."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Akbar Kurtha
Target entity description: Akbar Kurtha is a British actor known for his roles in film and television, including a main cast role in the science fiction series "Mars."
  • A. Jagat Singh
    Jagat Singh was a brother of Indian revolutionary Bhagat Singh, belonging to the same politically active Sandhu Jat Sikh family from Punjab.
  • B. Dinesh Chugtai
    Dinesh Chugtai is a socially awkward yet ambitious software engineer and programmer from the comedy TV series "Silicon Valley."
  • C. Gor Khatri
    Gor Khatri is a historic Mughal-era caravanserai and archaeological complex in Peshawar, Pakistan, known for its layers of ancient remains and religious significance over centuries.
  • D. Sher Afgan Khan
    Sher Afgan Khan was a Mughal nobleman and military officer best known as the first husband of the influential empress Nur Jahan.
  • E. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • 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_69aed931f5908190be2c07af66d4df25 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea61a63c819086e16b89d2ea2157 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f75f6c8190b9af77ed212a2774 completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b504a31de08190b543549a2b05b038 completed March 14, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_69b5084c8bd48190b7afc80bed196c90 completed March 14, 2026, 7:03 a.m.
Created at: March 9, 2026, 3:17 p.m.