Triple

T17915897
Position Surface form Disambiguated ID Type / Status
Subject Fer Servadou E447924 entity
Predicate alsoKnownAs P39 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: [Fer Servadou, alsoKnownAs, Fer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fer
Context triple: [Fer Servadou, alsoKnownAs, 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. Ferden
    Ferden is a small alpine municipality in the canton of Valais in southwestern Switzerland, known for its mountainous scenery and traditional Swiss village character.
  • E. 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.
  • 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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a3062bfc819083f7c0521bad4db8 completed April 19, 2026, 9:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a03212c9e88819099fb04040e543d63 completed May 12, 2026, 12:46 p.m.
Created at: April 10, 2026, 10:20 a.m.