Triple

T12362498
Position Surface form Disambiguated ID Type / Status
Subject SECCHI E294775 entity
Predicate hasComponent P35 FINISHED
Object COR2
COR2 is a coronagraph instrument in the SECCHI suite designed to image the outer solar corona and study coronal mass ejections.
 E977329 NE FINISHED

How this triple was built (4 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: COR2 | Statement: [SECCHI, hasComponent, COR2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: COR2
Context triple: [SECCHI, hasComponent, COR2]
  • A. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • B. C2r
    C2r is the standard magnetic polarity chron code assigned to the Gauss–Matuyama geomagnetic reversal interval in the geomagnetic polarity timescale.
  • C. CoR
    CoR is the commonly used abbreviation for the European Committee of the Regions, the EU’s advisory body representing local and regional authorities.
  • D. C-2
    C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • E. Cor
    Cor is a common Dutch diminutive or short form of the given name Cornelis.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: COR2
Triple: [SECCHI, hasComponent, COR2]
Generated description
COR2 is a coronagraph instrument in the SECCHI suite designed to image the outer solar corona and study coronal mass ejections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: COR2
Target entity description: COR2 is a coronagraph instrument in the SECCHI suite designed to image the outer solar corona and study coronal mass ejections.
  • A. COR
    COR is the IATA airport code for Ingeniero Aeronáutico Ambrosio L.V. Taravella International Airport serving Córdoba, Argentina.
  • B. C2r
    C2r is the standard magnetic polarity chron code assigned to the Gauss–Matuyama geomagnetic reversal interval in the geomagnetic polarity timescale.
  • C. CoR
    CoR is the commonly used abbreviation for the European Committee of the Regions, the EU’s advisory body representing local and regional authorities.
  • D. C-2
    C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • E. Cor
    Cor is a common Dutch diminutive or short form of the given name Cornelis.
  • F. None of above. chosen

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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f91a1908190a8a4fa9da3b47933 completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ab9ea4c81908313b11716ad7c43 completed May 2, 2026, 4:47 p.m.
NEDg Description generation batch_69f62c569a6c8190aecf8a4c627d8893 completed May 2, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_69f62d07d3148190a45542c8d43a7077 completed May 2, 2026, 4:57 p.m.
Created at: April 8, 2026, 9:54 p.m.