Triple

T15516811
Position Surface form Disambiguated ID Type / Status
Subject Fiber-fed Extended Range Optical Spectrograph E368854 entity
Predicate hasAcronym P43 FINISHED
Object FEROS E368855 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: FEROS | Statement: [Fiber-fed Extended Range Optical Spectrograph, hasAcronym, FEROS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FEROS
Context triple: [Fiber-fed Extended Range Optical Spectrograph, hasAcronym, FEROS]
  • A. FEROS chosen
    FEROS is a high-resolution echelle spectrograph used on ESO telescopes for precise stellar and exoplanet spectroscopy.
  • B. Fer
    Fer is a common shortened form of the given name Fernanda, often used as a casual or affectionate nickname.
  • C. Ferro
    Ferro is an alternative name for El Hierro, the smallest and westernmost of Spain’s Canary Islands in the Atlantic Ocean.
  • D. FEDRO
    FEDRO is the Swiss federal authority responsible for planning, constructing, operating, and maintaining the national road network.
  • E. Ferike
    Ferike is a Hungarian given name, often used as a diminutive form of names like Ferenc or Frederika.
  • 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_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e04033303c8190a87b6384f68a6921 completed April 16, 2026, 1:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d5111648190a61fc87170b0d93c completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:02 a.m.