Triple

T17575420
Position Surface form Disambiguated ID Type / Status
Subject Port of Salalah E428051 entity
Predicate nearby P350 FINISHED
Object city of Salalah NE NERFINISHED

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: city of Salalah | Statement: [Port of Salalah, nearby, city of Salalah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Salalah
Context triple: [Port of Salalah, nearby, city of Salalah]
  • A. Salalah chosen
    Salalah is a coastal city in southern Oman known for its monsoon-cooled climate, lush green landscapes, and role as a regional tourism and commercial hub.
  • B. Ha'il city
    Ha'il city is a major urban center in northwestern Saudi Arabia, known historically as a key stop on desert trade routes and today as the capital of the Ha'il Region.
  • C. Salha
    Salha is a Jordanian princess and member of the Hashemite royal family.
  • D. Saada city
    Saada city is a historic urban center in northern Yemen known for its traditional architecture and role as a stronghold of the Houthi movement.
  • E. Ash Shihr
    Ash Shihr is a coastal town in eastern Yemen historically known as a key port and commercial center in the Hadhramaut region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e463c88b3081908ddf6a2a12f6138e completed April 19, 2026, 5:10 a.m.
Created at: April 10, 2026, 5:50 a.m.