Triple

T7753884
Position Surface form Disambiguated ID Type / Status
Subject Sibi District E175840 entity
Predicate capital P234 FINISHED
Object Sibi E33029 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: Sibi | Statement: [Sibi District, capital, Sibi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sibi
Context triple: [Sibi District, capital, Sibi]
  • A. Sibi chosen
    Sibi is a historic town and district in the Balochistan region of Pakistan, known for its hot climate and traditional annual cattle and horse fair.
  • B. Sibari
    Sibari is a town in southern Italy’s Calabria region, located near the archaeological remains of the ancient Greek city of Sybaris.
  • C. Bhailsa
    Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
  • D. Sabya
    Sabya is a city in southwestern Saudi Arabia located within the Jazan Region near the Red Sea coast.
  • E. Sarabha
    Sarabha is an Indian surname most notably associated with Kartar Singh Sarabha, a prominent revolutionary in the Indian independence movement.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703d851d4819091e9117d3f34cb9a completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be5a649c81909c94d629348b34fc completed March 29, 2026, 5:53 a.m.
Created at: March 27, 2026, 4:08 p.m.