Triple
T6256679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jürgen |
E140183
|
entity |
| Predicate | cognateWith |
P2525
|
FINISHED |
| Object | George |
unclear NED1
|
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: George | Statement: [Jürgen, cognateWith, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Jürgen, cognateWith, George]
-
A.
George
George is the given name of George Brydges Rodney, an 18th-century British naval officer and admiral noted for his victories during the American Revolutionary War.
-
B.
George
George is the given name of George Armstrong Custer, the controversial U.S. Army officer and cavalry commander best known for his defeat and death at the Battle of the Little Bighorn.
-
C.
George
George is the given name of George Monck, a 17th-century English soldier and statesman instrumental in the Restoration of the monarchy under Charles II.
-
D.
George
George is the given name of George Monck, 1st Duke of Albemarle, a key English soldier and statesman who helped restore Charles II to the throne in 1660.
-
E.
George
George is a common English surname of likely Greek and Latin origin, associated with numerous notable historical and contemporary figures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69c008c95c5c819084bd3dd56133d84d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063653910819095f1dc3b90ce77db |
completed | March 22, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5191d2d248190b34edca246ee74b8 |
completed | March 26, 2026, 11:31 a.m. |
Created at: March 22, 2026, 4:24 p.m.