Triple

T4197552
Position Surface form Disambiguated ID Type / Status
Subject Lake of Tunis E85989 entity
Predicate adjacentTo P224 FINISHED
Object Radès E394133 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: Radès | Statement: [Lake of Tunis, adjacentTo, Radès]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Radès
Context triple: [Lake of Tunis, adjacentTo, Radès]
  • A. Radès chosen
    Radès is a coastal city in northern Tunisia known for its major sports facilities, including the national stadium that hosts prominent football clubs and international events.
  • B. Cité El Khadra
    Cité El Khadra is a residential and administrative neighborhood in the city of Tunis, Tunisia.
  • C. Medeba
    Medeba is an ancient city east of the Dead Sea, known from biblical accounts and later as a significant settlement in the region of Moab.
  • D. Larache
    Larache is a coastal city in northwestern Morocco, situated along the Atlantic Ocean and known for its historic medina and nearby ancient Phoenician-Roman archaeological site of Lixus.
  • E. Nouaceur
    Nouaceur is a town and municipality in the Casablanca-Settat region of Morocco, known for hosting Mohammed V International Airport.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0360bc8081908ceb2483eef89174 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a0ff2a08190ac7f89d306454ab8 completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:48 p.m.