Triple

T2570725
Position Surface form Disambiguated ID Type / Status
Subject Acre E57659 entity
Predicate alternativeName P39 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: [Acre, alternativeName, Akko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akko
Context triple: [Acre, alternativeName, 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. Tartus
    Tartus is a major Syrian port city on the Mediterranean coast that hosts Russia’s only naval facility outside the former Soviet Union.
  • C. 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.
  • D. Sidon Port
    Sidon Port is the historic harbor of the ancient Phoenician city of Sidon in modern-day Lebanon, long known as a key Mediterranean maritime and trade hub.
  • E. Eilat
    Eilat is Israel’s southernmost city and a major Red Sea resort and port known for its beaches, coral reefs, and tourism.
  • 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_69ab4a51410081908501dcf8bad9adc4 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd382928c8190b6316f3db48d8e73 completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69af656d7dec81909ea0aae4506cf4e3 completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:48 p.m.