Triple

T13633537
Position Surface form Disambiguated ID Type / Status
Subject Rakaposhi E325785 entity
Predicate near P350 FINISHED
Object Gilgit E86211 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: Gilgit | Statement: [Rakaposhi, near, Gilgit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilgit
Context triple: [Rakaposhi, near, Gilgit]
  • A. Gilgit chosen
    Gilgit is a major town in northern Pakistan that serves as a key regional hub for trade, tourism, and access to the Karakoram mountain range.
  • B. Skardu
    Skardu is a major town in northern Pakistan’s Gilgit-Baltistan region, known as a gateway to the Karakoram mountains and popular for its high-altitude trekking and scenic landscapes.
  • C. Khaplu
    Khaplu is a historic town in northern Pakistan’s Gilgit-Baltistan region, known as a gateway to the Karakoram mountains and for its traditional Balti culture and architecture.
  • D. Gilgiti Shina
    Gilgiti Shina is a regional variety of the Shina language spoken primarily in and around Gilgit in northern Pakistan.
  • E. Gilgit District
    Gilgit District is an administrative region in northern Pakistan’s Gilgit-Baltistan, known for its diverse ethnic communities and its location amid the high mountain ranges of the Karakoram and Himalayas.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a490508190924ac40f1dd519d6 completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d44e2148190a279aa6d103bf204 completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:51 p.m.