Triple

T25638361
Position Surface form Disambiguated ID Type / Status
Subject Euanthe E642767 entity
Predicate discoveredBy P412 FINISHED
Object Brian G. Marsden
Brian G. Marsden was a British astronomer renowned for his work in celestial mechanics and for directing the Minor Planet Center, where he specialized in tracking and predicting the orbits of comets and asteroids.
E1693139 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: Brian G. Marsden | Statement: [Euanthe, discoveredBy, Brian G. Marsden]
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: Brian G. Marsden
Triple: [Euanthe, discoveredBy, Brian G. Marsden]
Generated description
Brian G. Marsden was a British astronomer renowned for his work in celestial mechanics and for directing the Minor Planet Center, where he specialized in tracking and predicting the orbits of comets and asteroids.

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_69e77e7ce28081908b08d65ee6e5c8be completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fa64332081909df65f8b4380f152 completed May 2, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cbe6e6dc81908f4338caf7aa76ca completed May 22, 2026, 9:34 p.m.
NEDg Description generation batch_6a10cc64dde08190b02c25b583f4c264 completed May 22, 2026, 9:36 p.m.
NED2 Entity disambiguation (via description) batch_6a10ccf464b481909d0b12c1e24c5206 completed May 22, 2026, 9:39 p.m.
Created at: April 21, 2026, 5:37 p.m.