Triple

T14251726
Position Surface form Disambiguated ID Type / Status
Subject Aksaray Province E353283 entity
Predicate contains P35 FINISHED
Object Hasan Mountain E1086407 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: Hasan Mountain | Statement: [Aksaray Province, contains, Hasan Mountain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasan Mountain
Context triple: [Aksaray Province, contains, Hasan Mountain]
  • A. Hasan Mountain chosen
    Hasan Mountain is a prominent dormant stratovolcano in central Turkey, known for its distinctive twin-peaked summit and significance as a regional natural landmark.
  • B. Akbaba Peak
    Akbaba Peak is the tallest summit in Turkey’s Munzur Mountains, known for its rugged alpine terrain and scenic highland landscapes.
  • C. Gele Mountain
    Gele Mountain is a scenic and historically significant mountain area in Chongqing, China, known for its natural landscapes and former wartime sites.
  • D. Mount Barkan
    Mount Barkan is the highest peak in Israel’s Gilboa mountain range, known for its scenic views and surrounding nature reserves.
  • E. Achasan Mountain
    Achasan Mountain is a low, scenic peak on the outskirts of Seoul and Guri in South Korea, known for its easy hiking trails and panoramic views of the Han River and city skyline.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6296f9d0819086f62f525d07eb12 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd325a14b881909522b6fbbcc6326f completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:08 a.m.