Triple

T17307177
Position Surface form Disambiguated ID Type / Status
Subject Sur tribe E420192 entity
Predicate politicalCenter P4751 FINISHED
Object Sasaram E304744 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: Sasaram | Statement: [Sur tribe, politicalCenter, Sasaram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sasaram
Context triple: [Sur tribe, politicalCenter, Sasaram]
  • A. Sasaram chosen
    Sasaram is a historic town in eastern India known for its grand Mughal-era monuments, especially the tomb of Sher Shah Suri.
  • B. Hajipur
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • C. Saharanpur
    Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
  • D. Saharsa
    Saharsa is a city in the northeastern Indian state of Bihar, known as a major agricultural and commercial center in the Kosi river region.
  • E. Samastipur
    Samastipur is a city in the Indian state of Bihar known as an important railway junction and agricultural trade center in the region.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4390005dc81908345ebb6dd970582 completed April 19, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e0c1b881908aa2b6b4d8ac04b6 completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:43 a.m.