Triple

T16527650
Position Surface form Disambiguated ID Type / Status
Subject Rajkummar Rao E401481 entity
Predicate notableWork P4 FINISHED
Object Aligarh E93124 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: Aligarh | Statement: [Rajkummar Rao, notableWork, Aligarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aligarh
Context triple: [Rajkummar Rao, notableWork, Aligarh]
  • A. Aligarh chosen
    Aligarh is a prominent city in northern India known for its lock industry and as the home of Aligarh Muslim University.
  • B. Moradabad
    Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
  • C. Farrukhabad
    Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
  • D. Bareilly
    Bareilly is a historic city in the Indian state of Uttar Pradesh, known as a major center of the 1857 uprising against British colonial rule and now an important commercial and cultural hub.
  • E. Meerut
    Meerut is a historic city in the Indian state of Uttar Pradesh, known as the place where the Indian Rebellion of 1857 first erupted against British colonial rule.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed4b8a08190b5f179fc583001a6 completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01673979608190905afae3071413c0 completed May 11, 2026, 5:20 a.m.
Created at: April 10, 2026, 5:14 a.m.