Triple

T4970446
Position Surface form Disambiguated ID Type / Status
Subject Sher Shah Suri E111634 entity
Predicate capital P234 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: [Sher Shah Suri, capital, Sasaram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sasaram
Context triple: [Sher Shah Suri, capital, 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_69bd441a0eb481908050fa4273b19eae completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7213bf0081909b3c496f1804dc4c completed March 20, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba546a1081909fe082663ad5e238 completed March 21, 2026, 3:33 p.m.
Created at: March 20, 2026, 1:33 p.m.