Triple

T9097517
Position Surface form Disambiguated ID Type / Status
Subject Sachkhere Municipality E218064 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Sachkhere E97000 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: Sachkhere | Statement: [Sachkhere Municipality, hasAdministrativeCenter, Sachkhere]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sachkhere
Context triple: [Sachkhere Municipality, hasAdministrativeCenter, Sachkhere]
  • A. Sachkhere chosen
    Sachkhere is a town in western Georgia known as a local administrative and economic center in the Imereti region.
  • B. Sakesar
    Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
  • C. Chamkoria
    Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
  • D. Surkhob
    Surkhob is the historical name of a major river in Central Asia that forms part of what is now known as the Vakhsh River in Tajikistan.
  • E. Sehore
    Sehore is a town and district headquarters in central India, located near the state capital Bhopal in Madhya Pradesh.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b7d0d48190a3b15f35bef087e3 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0181a9ae88190ab80d4e80e919f42 completed April 3, 2026, 7:42 p.m.
Created at: March 30, 2026, 7:15 p.m.