Triple

T8460814
Position Surface form Disambiguated ID Type / Status
Subject Shivini E200033 entity
Predicate worshipCenter P14925 FINISHED
Object Tushpa E202064 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: Tushpa | Statement: [Shivini, worshipCenter, Tushpa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tushpa
Context triple: [Shivini, worshipCenter, Tushpa]
  • A. Tushpa chosen
    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.
  • B. Sheberghan
    Sheberghan is a city in northern Afghanistan that serves as a political and military stronghold of Uzbek leader Abdul Rashid Dostum.
  • C. Gundeshapur
    Gundeshapur was a prominent Sasanian city in southwestern Iran renowned as a major center of learning, medicine, and philosophy in late antiquity.
  • D. Afrasiab
    Afrasiab is a legendary Turanian king and formidable adversary of Iran in the Persian epic Shahnameh.
  • E. Sarakhs
    Sarakhs is a historic border city in northeastern Iran, known for its strategic location along ancient trade routes between Iran and Central Asia.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe49fca788190a8728ff74f4d26f5 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6e8ea2748190b9ffa2f36c0e397c completed April 3, 2026, 7:38 a.m.
Created at: March 30, 2026, 6:10 p.m.