Triple
T7940308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Emmett Brown |
E184371
|
entity |
| Predicate | pet |
P8711
|
FINISHED |
| Object | Copernicus |
E422246
|
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: Copernicus | Statement: [Dr. Emmett Brown, pet, Copernicus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Copernicus Context triple: [Dr. Emmett Brown, pet, Copernicus]
-
A.
Copernicus
chosen
Copernicus is the European Union’s flagship Earth observation programme that uses satellites and ground-based systems to monitor and provide data on the planet’s environment, climate, and security.
-
B.
Coperni
Coperni is a contemporary Paris-based fashion label known for its innovative, tech-influenced designs and viral runway moments.
-
C.
Képler
Képler is a given name associated with the individual known as Pepe.
-
D.
Galileo
Galileo is the European Union's global navigation satellite system designed to provide highly accurate positioning and timing services worldwide.
-
E.
Galileo
Galileo is a popular German television knowledge magazine show that presents scientific, technological, and everyday topics in an accessible, entertaining format.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0ac8bc8190b4e4f79b15c316b3 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c0e868481908748d340244ea8ea |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:08 p.m.