Triple

T15016824
Position Surface form Disambiguated ID Type / Status
Subject Western Lebanon E377978 entity
Predicate hasMajorCity P316 FINISHED
Object Tyre E30369 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: Tyre | Statement: [Western Lebanon, hasMajorCity, Tyre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyre
Context triple: [Western Lebanon, hasMajorCity, Tyre]
  • A. Tyre chosen
    Tyre is an ancient Phoenician port city, in present-day Lebanon, renowned as a major maritime, commercial, and cultural center of the Mediterranean world.
  • B. Tarsos
    Tarsos is the ancient name of the historic city of Tarsus in Cilicia, a significant cultural and commercial center in the eastern Mediterranean world.
  • C. Suret
    Suret is a modern Eastern Neo-Aramaic language spoken primarily by Assyrian communities in parts of Iraq, Syria, Iran, and the global diaspora.
  • D. Tournor
    Tournor is a surname variant of "Turnor," typically of English origin.
  • E. Trun
    Trun is a commune in northwestern France that became historically significant as a focal point in the closing encirclement of German forces during the Battle of the Falaise Pocket in World War II.
  • 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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7633fcc8190b2231f43252bc46f completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9692e4fc8190a1194a41fc8a832c completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:55 a.m.