Triple

T14512393
Position Surface form Disambiguated ID Type / Status
Subject Batman Province E340428 entity
Predicate hasNotableHistoricalSite P1098 FINISHED
Object Hasankeyf E1186902 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: Hasankeyf | Statement: [Batman Province, hasNotableHistoricalSite, Hasankeyf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasankeyf
Context triple: [Batman Province, hasNotableHistoricalSite, Hasankeyf]
  • A. Hasankeyf chosen
    Hasankeyf is an ancient town in southeastern Turkey renowned for its rich archaeological heritage and dramatic setting along the Tigris River.
  • B. Seydikemer
    Seydikemer is a rural district and town in southwestern Turkey known for its agricultural landscape and proximity to popular coastal and historical sites in Muğla Province.
  • C. Gemlik
    Gemlik is a coastal town and district in Bursa Province, northwestern Turkey, known for its port on the Sea of Marmara and its olive production.
  • D. Suşehri
    Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
  • E. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6c6054819086b4c0ce1d83fdc5 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf0743288190b3bec8c48b5c7893 completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 1:21 a.m.