Triple

T4139073
Position Surface form Disambiguated ID Type / Status
Subject Hazara E89227 entity
Predicate hasTown P847 FINISHED
Object Battagram E271511 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: Battagram | Statement: [Hazara, hasTown, Battagram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Battagram
Context triple: [Hazara, hasTown, Battagram]
  • A. Battagram chosen
    Battagram is a town and district headquarters in Pakistan’s Khyber Pakhtunkhwa province, known for its mountainous terrain and location along the Karakoram Highway.
  • B. Stryama
    Stryama is a river in Bulgaria that flows through the central part of the country before joining the Maritsa River.
  • C. Negaraku
    Negaraku is the national anthem of Malaysia, symbolizing the country's sovereignty and unity.
  • D. Barshaini
    Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
  • E. Humera
    Humera is a town in northwestern Ethiopia near the borders with Eritrea and Sudan, known for its strategic location and sesame production.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02485a788190ba6ee769e663b2d3 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576c9f8a081908c2910ac475e4974 completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:43 p.m.