Triple

T25238935
Position Surface form Disambiguated ID Type / Status
Subject Do Bigha Zamin E632411 entity
Predicate screenwriter P2831 FINISHED
Object Paul Mahendra
Paul Mahendra is a screenwriter best known for his work on the landmark Indian social-realist film "Do Bigha Zamin."
E1673328 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: Paul Mahendra | Statement: [Do Bigha Zamin, screenwriter, Paul Mahendra]
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: Paul Mahendra
Triple: [Do Bigha Zamin, screenwriter, Paul Mahendra]
Generated description
Paul Mahendra is a screenwriter best known for his work on the landmark Indian social-realist film "Do Bigha Zamin."

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_69e75a8ec5f88190b9eba06ae42b413a completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47dfc523c8190b61295b451d1e5cd completed May 1, 2026, 10:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067e3e91c8190a8679bb991489c63 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1068d6b1e08190926bfecdefed6a95 completed May 22, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a106963fc1c81909354c25da5f000f6 completed May 22, 2026, 2:34 p.m.
Created at: April 21, 2026, 1:07 p.m.