Triple

T28091954
Position Surface form Disambiguated ID Type / Status
Subject Soyuz TM-31 E709975 entity
Predicate spacecraftSerialNumber P35657 FINISHED
Object Soyuz TM No. 204
Soyuz TM No. 204 is the specific Soyuz TM-series spacecraft used for the Soyuz TM-31 mission, which carried the first resident crew to the International Space Station.
E1858030 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: Soyuz TM No. 204 | Statement: [Soyuz TM-31, spacecraftSerialNumber, Soyuz TM No. 204]
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: Soyuz TM No. 204
Triple: [Soyuz TM-31, spacecraftSerialNumber, Soyuz TM No. 204]
Generated description
Soyuz TM No. 204 is the specific Soyuz TM-series spacecraft used for the Soyuz TM-31 mission, which carried the first resident crew to the International Space Station.

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_69ef9b70fd108190a875953b2e50ca91 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6406afe448190ad9c61220d2573b4 completed May 2, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2588f707148190b72827500a4c7dee completed June 7, 2026, 3:06 p.m.
NEDg Description generation batch_6a258f33e3d081909b817177fe6be30e completed June 7, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a258f8e1638819080500d9c5d777c07 completed June 7, 2026, 3:34 p.m.
Created at: April 27, 2026, 8:59 p.m.