Triple

T17066044
Position Surface form Disambiguated ID Type / Status
Subject Yafran E414090 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Gharyan E418922 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: Gharyan | Statement: [Yafran, hasNearbySettlement, Gharyan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gharyan
Context triple: [Yafran, hasNearbySettlement, Gharyan]
  • A. Gharyan chosen
    Gharyan is a major town in northwestern Libya, known as an administrative and commercial center in the Nafusa Mountains region.
  • B. Ghawwas
    Ghawwas is a notable poet associated with the Dakhni (Deccani) literary tradition of South Asia.
  • C. Al Ghaydah
    Al Ghaydah is a coastal city in eastern Yemen that serves as the administrative and commercial center of the Mahra Governorate near the border with Oman.
  • D. Al-Kharj
    Al-Kharj is a city in central Saudi Arabia, southeast of Riyadh, known for its agricultural production and growing urban development.
  • E. Farwaniya
    Farwaniya is a major residential and commercial district in Kuwait, known for its dense population and role as a key urban center near Kuwait City.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3db8171348190ab68d2e4f05f7120 completed April 18, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0123509e1481908cfc304b02fe8632 completed May 11, 2026, 12:31 a.m.
Created at: April 10, 2026, 5:34 a.m.