Triple

T18747273
Position Surface form Disambiguated ID Type / Status
Subject Red Sea trade corridor E458435 entity
Predicate includesPort P65472 FINISHED
Object Suakin 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: Suakin | Statement: [Red Sea trade corridor, includesPort, Suakin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suakin
Context triple: [Red Sea trade corridor, includesPort, Suakin]
  • A. Suakin chosen
    Suakin is a historic port city on Sudan’s Red Sea coast that was once a major hub for trade and pilgrimage between Africa and the Arabian Peninsula.
  • B. Sakaar
    Sakaar is a chaotic, trash-covered planet ruled by the Grandmaster in the Marvel Cinematic Universe, known for its gladiatorial contests and bizarre cosmic detritus.
  • C. Sukeva
    Sukeva is a village in northern Finland best known for housing the Sukevan vankila prison facility.
  • D. Senyavin
    Senyavin is a Russian surname most notably associated with a family of naval officers and admirals in the Imperial Russian Navy.
  • E. Surlej
    Surlej is a small hamlet in the municipality of Silvaplana in Switzerland’s Upper Engadine region, known for its scenic alpine setting near Lake Silvaplana.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e576936cf08190b3c0d2f4e8a616fc completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.