Triple

T16912448
Position Surface form Disambiguated ID Type / Status
Subject Fernando E410234 entity
Predicate hasShortForm P43 FINISHED
Object Fer E990808 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: Fer | Statement: [Fernando, hasShortForm, Fer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fer
Context triple: [Fernando, hasShortForm, Fer]
  • A. Fer chosen
    Fer is a common shortened form of the given name Fernanda, often used as a casual or affectionate nickname.
  • B. Ferike
    Ferike is a Hungarian given name, often used as a diminutive form of names like Ferenc or Frederika.
  • C. Ferch
    Ferch is a small village in the Brandenburg region of Germany, known for its lakeside setting on Schwielowsee and its traditional rural character.
  • D. Ferla
    Ferla is a small historic town in southeastern Sicily, Italy, known as a gateway to the UNESCO-listed Pantalica archaeological area and its surrounding natural landscapes.
  • E. Feraud
    Feraud is a French surname most notably associated with the character Gabriel Feraud from Joseph Conrad’s novella “The Duel” and its film adaptation “The Duellists.”
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3e6b9481909fbaeb0bddd7e3b2 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7bb4ac481909318d3d61a2d10e1 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.