Triple

T31153637
Position Surface form Disambiguated ID Type / Status
Subject Viktor Ambartsumian E794143 entity
Predicate hasAsteroidNamedAfter P17121 FINISHED
Object 1905 Ambartsumian
1905 Ambartsumian is a main-belt asteroid named in honor of the Armenian astrophysicist Viktor Ambartsumian, a pioneer in theoretical astrophysics and the study of stellar associations.
E1951752 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: 1905 Ambartsumian | Statement: [Viktor Ambartsumian, hasAsteroidNamedAfter, 1905 Ambartsumian]
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: 1905 Ambartsumian
Triple: [Viktor Ambartsumian, hasAsteroidNamedAfter, 1905 Ambartsumian]
Generated description
1905 Ambartsumian is a main-belt asteroid named in honor of the Armenian astrophysicist Viktor Ambartsumian, a pioneer in theoretical astrophysics and the study of stellar associations.

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_69f224d41bb48190a5621cd1485e3a30 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697f2086481908e0d6730e978c345 completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29590701b08190887e806682c6412d completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a2960b425c88190bb9bebbbbf63ac02 completed June 10, 2026, 1:03 p.m.
NED2 Entity disambiguation (via description) batch_6a29619e4d6c819095f3a0169a9779e2 completed June 10, 2026, 1:07 p.m.
Created at: April 29, 2026, 9:06 p.m.