Triple

T15550297
Position Surface form Disambiguated ID Type / Status
Subject Riyom E370724 entity
Predicate near P350 FINISHED
Object Jos E59896 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: Jos | Statement: [Riyom, near, Jos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jos
Context triple: [Riyom, near, Jos]
  • A. Jos chosen
    Jos is a major city in central Nigeria known for its relatively temperate climate, tin mining history, and role as an administrative and commercial center.
  • B. Jo
    Jo is a given name used across various cultures, often as a short form of names like Joseph, Joanna, or Jonathan.
  • C. Jud
    Jud is a masculine given name, often used as a short form of names like Judson or Judah.
  • D. Josh
    Josh is a character in the horror film "Midsommar," portrayed as one of the American graduate students who travel to a remote Swedish commune for a midsummer festival that turns increasingly disturbing.
  • E. Josh
    Josh is a fictional political operative best known as the sharp-witted Deputy White House Chief of Staff on the television series "The West Wing."
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a93121881909d88ca55a39252ac completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455dfbcc8190a93e90c59b2d3045 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:08 a.m.