Triple

T36096478

Position	Surface form	Disambiguated ID	Type / Status
Subject	Progress M-34	`E1044075`	entity
Predicate	targetModule	`P111154`	FINISHED
Object	Spektr module of Mir The Spektr module of the Mir space station was a Russian-built research and living module primarily used for Earth observation and scientific experiments, and was heavily damaged in a 1997 collision with a Progress cargo spacecraft.	`E2168377`	NE FINISHED

How this triple was built (3 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: Spektr module of Mir | Statement: [Progress M-34, targetModule, Spektr module of Mir]

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: Spektr module of Mir
Triple: [Progress M-34, targetModule, Spektr module of Mir]

Generated description

The Spektr module of the Mir space station was a Russian-built research and living module primarily used for Earth observation and scientific experiments, and was heavily damaged in a 1997 collision with a Progress cargo spacecraft.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: targetModule
Context triple: [Progress M-34, targetModule, Spektr module of Mir]

A. moduleOf
Indicates that one entity functions as a component or sub-unit that belongs to, or is contained within, another larger entity.
B. moduleType
Indicates the classification or category of a module in terms of its functional or structural type.
C. coreModule
Indicates that something functions as a primary or foundational module within a larger system or structure.
D. targetUnit chosen
Indicates that one entity serves as the specific unit or object that another entity is directed at, operates on, or is intended to affect.
E. targetFeature
Indicates that one entity is the specific feature, attribute, or characteristic that another entity is directed toward, focused on, or intended to affect.
F. None of above.

Provenance (6 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_69f76e32d60c8190ba781ffaaab4aa3d`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69feff70fbec8190b1ff5f943f29613e`	completed	May 9, 2026, 9:33 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a38d54aab248190a865e10399e92f5a`	completed	June 22, 2026, 6:25 a.m.
NEDg	Description generation	`batch_6a38d5e83b58819080bd6a95a17f6b2b`	completed	June 22, 2026, 6:27 a.m.
NED2	Entity disambiguation (via description)	`batch_6a38d681cf388190896a30e2b0939181`	completed	June 22, 2026, 6:30 a.m.
PD	Predicate disambiguation	`batch_69fefbcd5b7881909cfe52b32f8a4301`	completed	May 9, 2026, 9:18 a.m.

Created at: May 3, 2026, 4:08 p.m.