Triple

T12920685
Position Surface form Disambiguated ID Type / Status
Subject Ahal Region E309109 entity
Predicate containsMountainRange P651 FINISHED
Object Kopet Dag E332078 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: Kopet Dag | Statement: [Ahal Region, containsMountainRange, Kopet Dag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kopet Dag
Context triple: [Ahal Region, containsMountainRange, Kopet Dag]
  • A. Kopet Dag chosen
    Kopet Dag is a mountain range in Central Asia forming a natural border between northeastern Iran and southern Turkmenistan.
  • B. Kopsenni
    Kopsenni is the highest peak on the Faroe Islands' main island of Streymoy, known for its rugged terrain and scenic North Atlantic views.
  • C. Karlaplan
    Karlaplan is a prominent circular plaza and park with a central fountain in the Östermalm district of Stockholm, Sweden.
  • D. Namsos
    Namsos is a coastal town and municipality in central Norway known for its timber industry, fjord-side location, and role as a regional service center in Trøndelag.
  • E. Kopaska
    Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971e7f6e881908c7bb12283898c80 completed April 10, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af5ffcc48190bf93ce32e4aecfcd completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:41 p.m.