Triple

T7776747
Position Surface form Disambiguated ID Type / Status
Subject Harari houses E221412 entity
Predicate locatedIn P40 FINISHED
Object Harar E221406 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: Harar | Statement: [Harari houses, locatedIn, Harar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harar
Context triple: [Harari houses, locatedIn, Harar]
  • A. Harar chosen
    Harar is a historic fortified city in eastern Ethiopia renowned for its ancient Islamic heritage, distinctive city walls, and status as a UNESCO World Heritage Site.
  • B. Arafo
    Arafo is a small municipality on the island of Tenerife in Spain’s Canary Islands, known for its rural landscapes and traditional Canarian character.
  • C. Burao
    Burao is a key commercial and administrative city in central Somaliland, known as a major livestock trading hub in the region.
  • D. Gash‑Barka
    Gash‑Barka is a largely agricultural region in southwestern Eritrea known for its fertile land and role as one of the country’s main food-producing areas.
  • E. Dakhla
    Dakhla is a coastal city in Western Sahara known for its strategic Atlantic location, fishing industry, and popularity as a wind- and kitesurfing destination.
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d22ee081908081b5f5ecdb4d39 completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69cd66d1507c8190a84a69cd0130bb3b completed April 1, 2026, 6:41 p.m.
Created at: March 30, 2026, 4:11 p.m.