Triple

T30842972
Position Surface form Disambiguated ID Type / Status
Subject Leica screw-mount lenses (via adapter on M bodies) E785559 entity
Predicate compatibleWithCamera P184006 FINISHED
Object Leica CLE
The Leica CLE is a compact 35mm rangefinder camera, co-developed with Minolta, that offers aperture-priority autoexposure and accepts Leica M-mount lenses.
E1941253 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: Leica CLE | Statement: [Leica screw-mount lenses (via adapter on M bodies), compatibleWithCamera, Leica CLE]
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: Leica CLE
Triple: [Leica screw-mount lenses (via adapter on M bodies), compatibleWithCamera, Leica CLE]
Generated description
The Leica CLE is a compact 35mm rangefinder camera, co-developed with Minolta, that offers aperture-priority autoexposure and accepts Leica M-mount lenses.

Provenance (5 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_69f224b850848190a4af4ccf8ddadcdf completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f7ab7a0910819093a77bd62c47a99d completed May 3, 2026, 8:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3056dc75808190af961caa14d3155c completed June 15, 2026, 7:47 p.m.
NEDg Description generation batch_6a305a01e84c8190af47c8b3611badb5 completed June 15, 2026, 8:01 p.m.
NED2 Entity disambiguation (via description) batch_6a305b1109088190850b5ac064319e05 completed June 15, 2026, 8:05 p.m.
Created at: April 29, 2026, 8:45 p.m.