Triple

T22868375
Position Surface form Disambiguated ID Type / Status
Subject Aghvank E567118 entity
Predicate religiousCenter P1191 FINISHED
Object Partav 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: Partav | Statement: [Aghvank, religiousCenter, Partav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Partav
Context triple: [Aghvank, religiousCenter, Partav]
  • A. Partav chosen
    Partav was a major historical city in the Caucasus region, serving as a key political and cultural center of Caucasian Albania.
  • B. Karashahr
    Karashahr is an ancient oasis town in Xinjiang, China, historically significant as a Silk Road hub and a key center of the Indo-European–speaking Tocharian culture.
  • C. 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.
  • D. Khorog
    Khorog is a remote mountain town in eastern Tajikistan that serves as the capital of the Gorno-Badakhshan Autonomous Region and a key hub in the Pamir Mountains.
  • E. Girgit
    Girgit is a popular Tulu-language comedy thriller film known for its humorous take on contemporary coastal Karnataka life.
  • 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_69e24589d8348190b96422d13a678bc1 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17f02c8b8819095cbee626f935fed completed April 29, 2026, 3:46 a.m.
Created at: April 17, 2026, 3:38 p.m.