Triple
T6639343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl-Henrik Robèrt |
E150545
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Robèrt |
E2918
|
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: Robèrt | Statement: [Karl-Henrik Robèrt, familyName, Robèrt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robèrt Context triple: [Karl-Henrik Robèrt, familyName, Robèrt]
-
A.
Robert
chosen
Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
B.
Geoffrey
Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
-
C.
Rowland
Rowland is the namesake of the Jonsson-Rowland Science Center, likely a notable figure in science or education commemorated by the institution.
-
D.
Rowland
Rowland is the given name of R. H. Macy, the 19th-century American businessman who founded the Macy's department store chain.
-
E.
Bobert
Bobert is a robotic student character from the animated television series "The Amazing World of Gumball," known for his literal, emotionless personality and advanced technological abilities.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aff1fe8081908c32db341b0fb354 |
completed | March 27, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e455edb88190983f74f39e55665c |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2 p.m.