Triple

T20837204
Position Surface form Disambiguated ID Type / Status
Subject Nad Ali E512989 entity
Predicate borderingDistrict P224 FINISHED
Object Marjah NE NERFINISHED

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: Marjah | Statement: [Nad Ali, borderingDistrict, Marjah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marjah
Context triple: [Nad Ali, borderingDistrict, Marjah]
  • A. Marjah chosen
    Marjah is a rural agricultural town in southern Afghanistan that gained international attention as a major Taliban stronghold and the focus of a large NATO offensive in 2010.
  • B. Kunduz
    Kunduz is a strategically important city in northern Afghanistan known for its contested control during the Afghan conflict and its role as a regional commercial and transport hub.
  • C. Kandahar
    Kandahar is a historic city in southern Afghanistan that has long served as a major political, cultural, and commercial center in the region.
  • D. Kafr Takharim
    Kafr Takharim is a town in northwestern Syria known for its location in the Idlib region and its involvement in the Syrian civil conflict.
  • E. خيبر
    خيبر واحة تاريخية في شمال غرب الجزيرة العربية اشتهرت بحصونها ومعركتها الشهيرة في صدر الإسلام.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3280a1881909a86d1fe498aee50 completed April 21, 2026, 12:22 a.m.
Created at: April 16, 2026, 12:42 p.m.