Triple

T19606730
Position Surface form Disambiguated ID Type / Status
Subject Taba Border Crossing E470624 entity
Predicate connectsCity P4245 FINISHED
Object Taba 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: Taba | Statement: [Taba Border Crossing, connectsCity, Taba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taba
Context triple: [Taba Border Crossing, connectsCity, Taba]
  • A. Taba chosen
    Taba is a small Egyptian resort town on the Red Sea near the border with Israel, known for its beaches, coral reefs, and role as a popular gateway between the two countries.
  • B. Taba-ao
    Taba-ao is a barangay (village-level administrative division) of the municipality of Sagay in the Philippines.
  • C. Qataban
    Qataban was an ancient South Arabian kingdom known for its incense trade and strategic position along key caravan routes in what is now Yemen.
  • D. Tchaman
    Tchaman is a Kwa language of the Central Tano branch spoken primarily by the Tchaman (Ébrié) people in southern Côte d’Ivoire.
  • E. Labweh
    Labweh is a town in northeastern Lebanon situated within the Baalbek-Hermel Governorate, known for its agricultural surroundings and proximity to the Syrian border.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640c7ed24819091502fe0d5e139bc completed April 20, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:43 p.m.