Triple

T17089567
Position Surface form Disambiguated ID Type / Status
Subject Abeïbara E414687 entity
Predicate locatedIn P40 FINISHED
Object Sahara Desert E10378 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: Sahara Desert | Statement: [Abeïbara, locatedIn, Sahara Desert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sahara Desert
Context triple: [Abeïbara, locatedIn, Sahara Desert]
  • A. Sahara Desert chosen
    The Sahara Desert is the world’s largest hot desert, spanning much of North Africa with vast sand seas, rocky plateaus, and extreme arid conditions.
  • B. Sahara
    Sahara is an OpenStack data processing service that provisions and manages Hadoop and other big data clusters on cloud infrastructure.
  • C. Sahara
    "Sahara" is a 2005 action-adventure film based on Clive Cussler's novel, following treasure hunters on a perilous quest in the African desert.
  • D. Sahara
    "Sahara" is a landmark 1972 jazz album by pianist McCoy Tyner, acclaimed for its expansive compositions and innovative blend of modal jazz with African and Eastern influences.
  • E. Sahara
    Sahara is a popular mid- to high-level Jeep Wrangler trim package known for its comfort-oriented features and distinctive styling suited for both on- and off-road driving.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbe9dc808190ab20537100e7ddee completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ee9fd108190b12e8624bb66caf2 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:35 a.m.