Triple

T20066678
Position Surface form Disambiguated ID Type / Status
Subject Greater Tehran E499624 entity
Predicate contains P35 FINISHED
Object Hashtgerd 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: Hashtgerd | Statement: [Greater Tehran, contains, Hashtgerd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hashtgerd
Context triple: [Greater Tehran, contains, Hashtgerd]
  • A. Hashtgerd chosen
    Hashtgerd is a city in northern Iran that serves as an important urban center and gateway within Alborz Province, located west of Tehran.
  • B. Kharas
    Kharas is a Palestinian village located in the Hebron Governorate in the southern West Bank.
  • C. Margiana
    Margiana was an ancient historical region in Central Asia, centered on the oasis city of Merv and known for its role as a key hub along the Silk Road.
  • D. Khorasan
    Khorasan is a historical region in northeastern Iran and surrounding areas that served as a major cultural and political center in various Persian and Islamic empires.
  • E. Luristan
    Luristan is a historical region in western Iran, known for its mountainous terrain, Lur ethnic population, and distinctive ancient bronze artifacts.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66379f2cc81908f13a7b216878f12 completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.