Triple

T10939842
Position Surface form Disambiguated ID Type / Status
Subject Recklinghausen E258438 entity
Predicate hasTwinTown P919 FINISHED
Object Akko E100560 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: Akko | Statement: [Recklinghausen, hasTwinTown, Akko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akko
Context triple: [Recklinghausen, hasTwinTown, Akko]
  • A. Akko chosen
    Akko is an ancient port city in northern Israel known for its well-preserved Crusader and Ottoman architecture and its designation as a UNESCO World Heritage Site.
  • B. Kfarakka
    Kfarakka is a village in northern Lebanon situated within the Koura District, known for its agricultural character and traditional rural life.
  • C. Tartus
    Tartus is a major Syrian port city on the Mediterranean coast that hosts Russia’s only naval facility outside the former Soviet Union.
  • D. Sidon
    Sidon is an ancient Phoenician port city, located in present-day Lebanon, that was a major center of maritime trade and culture in the eastern Mediterranean.
  • E. عكّا
    عكّا هي مدينة تاريخية ساحلية في شمال فلسطين/إسرائيل تشتهر بقلعتها وأسوارها العثمانية ومينائها القديم وتراثها المتعدد الثقافات.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c1389881909341170984211810 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c0e940081908c84ea4cf3b877fc completed April 17, 2026, 1:56 p.m.
Created at: April 8, 2026, 9:23 p.m.