Triple

T4007231
Position Surface form Disambiguated ID Type / Status
Subject Karura Forest E89553 entity
Predicate near P350 FINISHED
Object Gigiri E89552 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: Gigiri | Statement: [Karura Forest, near, Gigiri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gigiri
Context triple: [Karura Forest, near, Gigiri]
  • A. Gigiri chosen
    Gigiri is an affluent diplomatic and residential district in Nairobi, Kenya, known for hosting major international institutions and embassies.
  • B. Meru
    Meru is a town in eastern Kenya that serves as a commercial and administrative hub for the surrounding agricultural region near Mount Kenya.
  • C. Kiliwa
    Kiliwa is an indigenous people of northern Baja California, Mexico, known for their distinct Yuman language and traditional hunter-gatherer culture.
  • D. Kili
    Kili is a young Dwarf prince of Durin's line and a member of Thorin Oakenshield's company in J.R.R. Tolkien's Middle-earth legendarium.
  • E. Mount Meru
    Mount Meru is a dormant stratovolcano in northern Tanzania, renowned as one of Africa’s highest peaks and a prominent feature near Arusha and Mount Kilimanjaro.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa62d0e081909aaed2978a840734 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5768fae4881908c9dea4e39e3788c completed March 14, 2026, 2:54 p.m.
Created at: March 9, 2026, 3:34 p.m.