Triple
T18498678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Études galiléennes |
E452011
|
entity |
| Predicate | mainSubject |
P3
|
FINISHED |
| Object | Galileo Galilei |
—
|
NE NERFINISHED |
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: Galileo Galilei | Statement: [Études galiléennes, mainSubject, Galileo Galilei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Galileo Galilei Context triple: [Études galiléennes, mainSubject, Galileo Galilei]
-
A.
Galileo Galilei
chosen
Galileo Galilei was an Italian Renaissance astronomer, physicist, and engineer whose pioneering use of the telescope and support for heliocentrism helped lay the foundations of modern science.
-
B.
Galileo
Galileo was a NASA space probe that studied Jupiter and its moons in detail during the 1990s and early 2000s.
-
C.
Galileo
Galileo was a legendary Irish Thoroughbred racehorse and influential sire, renowned for winning the 2001 Epsom Derby and becoming one of the most important stallions in modern racing and breeding.
-
D.
Galileo
Galileo is a popular German television knowledge magazine show that presents scientific, technological, and everyday topics in an accessible, entertaining format.
-
E.
Galileo
Galileo is a major global distribution system used worldwide by travel agencies and airlines to access and manage airline, hotel, and other travel-related bookings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c275388190aafe891d0202f82e |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.