Triple

T25049422
Position Surface form Disambiguated ID Type / Status
Subject X-ray microscopy E627333 entity
Predicate usesOptics P134872 FINISHED
Object Kirkpatrick–Baez mirrors
Kirkpatrick–Baez mirrors are a pair of orthogonally arranged, curved reflective surfaces used to tightly focus X-rays for high-resolution imaging and analysis.
 E1664626 NE FINISHED

How this triple was built (3 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: Kirkpatrick–Baez mirrors | Statement: [X-ray microscopy, usesOptics, Kirkpatrick–Baez mirrors]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kirkpatrick–Baez mirrors
Triple: [X-ray microscopy, usesOptics, Kirkpatrick–Baez mirrors]
Generated description
Kirkpatrick–Baez mirrors are a pair of orthogonally arranged, curved reflective surfaces used to tightly focus X-rays for high-resolution imaging and analysis.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: usesOptics
Context triple: [X-ray microscopy, usesOptics, Kirkpatrick–Baez mirrors]
  • A. usesOpticsType
    Indicates that one entity employs or is characterized by a specific type of optical system or technology.
  • B. hasOpticalElement chosen
    Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
  • C. opticalDesign
    Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
  • D. usesAsLens
    Indicates that one entity employs another entity as a lens or optical element through which to view, focus, or modify light or images.
  • E. usesLensMount
    Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
  • F. None of above.

Provenance (6 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_69e2ff2b4c80819087c916b2b16241b9 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f4549e7df48190aa0642008f748314 completed May 1, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048c9f0508190b3d10208b112016b completed May 22, 2026, 12:15 p.m.
NEDg Description generation batch_6a104cbac0b48190ac739e35c090180f completed May 22, 2026, 12:31 p.m.
NED2 Entity disambiguation (via description) batch_6a104d2be4f08190a7a94bc1b04223cf completed May 22, 2026, 12:33 p.m.
PD Predicate disambiguation batch_69f44d77f6e88190a4643ab2cbef567b completed May 1, 2026, 6:51 a.m.
Created at: April 18, 2026, 6:08 a.m.