Triple

T11433690
Position Surface form Disambiguated ID Type / Status
Subject Mardan campus E270950 entity
Predicate locatedIn P40 FINISHED
Object Mardan E54093 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: Mardan | Statement: [Mardan campus, locatedIn, Mardan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mardan
Context triple: [Mardan campus, locatedIn, Mardan]
  • A. Mardan chosen
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • B. Balkh
    Balkh is an ancient city in northern Afghanistan, historically a major center of Persian culture, trade, and Islamic scholarship.
  • C. Daykundi
    Daykundi is a central Afghan province within the Hazarajat region, known for its predominantly Hazara population and mountainous terrain.
  • D. Zhob
    Zhob is a town and district in northwestern Balochistan, Pakistan, known historically as a strategic frontier outpost and regional trade center near the Afghan border.
  • E. Tushpa
    Tushpa was the ancient fortified city on the eastern shore of Lake Van that served as the political and cultural center of the Kingdom of Urartu in the early first millennium BCE.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c485f481909dd3d9b0993f3faf completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e624782cf88190b696a1c7c9a56395 completed April 20, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:35 p.m.