Triple

T21557619
Position Surface form Disambiguated ID Type / Status
Subject Koura E531933 entity
Predicate borderedBy P224 FINISHED
Object Tripoli District 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: Tripoli District | Statement: [Koura, borderedBy, Tripoli District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tripoli District
Context triple: [Koura, borderedBy, Tripoli District]
  • A. Tobruk District
    Tobruk District is an administrative region in eastern Libya centered on the port city of Tobruk, known for its strategic coastal location and historical significance.
  • B. Tripoli
    Tripoli was a historic American shipyard and port city involved in constructing naval vessels such as the USS Intrepid.
  • C. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • D. Tripoli chosen
    Tripoli is Lebanon’s second-largest city, a historic Mediterranean port known for its medieval Mamluk architecture and vibrant commercial life.
  • E. Tripoli
    Tripoli is a historic city in the central Peloponnese of Greece that serves as the main urban and administrative center of the Arcadia 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eed2e14af88190bc70b4d0f3453aac completed April 27, 2026, 3:07 a.m.
Created at: April 16, 2026, 6:29 p.m.