Triple
T36863313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soyuz 11 |
E911001
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object |
Soyuz 12
Soyuz 12 was a 1973 Soviet crewed spaceflight that tested a redesigned, safer Soyuz spacecraft in Earth orbit following the Soyuz 11 accident.
|
E2252288
|
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 12 | Statement: [Soyuz 11, followedBy, Soyuz 12]
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 12 Triple: [Soyuz 11, followedBy, Soyuz 12]
Generated description
Soyuz 12 was a 1973 Soviet crewed spaceflight that tested a redesigned, safer Soyuz spacecraft in Earth orbit following the Soyuz 11 accident.
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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cfd23a708190b4b095bab8735168 |
completed | May 3, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4154197f6081908eb11aa428ad8e94 |
completed | June 28, 2026, 5:04 p.m. |
| NEDg | Description generation | batch_6a41547f79608190ad6047b8fb2c57d4 |
completed | June 28, 2026, 5:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a4154d8aef8819094b20ba27401113c |
completed | June 28, 2026, 5:07 p.m. |
Created at: May 3, 2026, 4:13 p.m.