Triple
T16221777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eton language |
E393743
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Beti-Eton |
E1200462
|
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: Beti-Eton | Statement: [Eton language, hasAlternativeName, Beti-Eton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beti-Eton Context triple: [Eton language, hasAlternativeName, Beti-Eton]
-
A.
Eton (Beti)
chosen
Eton (Beti) is a Bantu language spoken primarily by the Beti people in central Cameroon.
-
B.
Eton
Eton is a small city in Murray County, Georgia, known for its rural character and proximity to the Appalachian foothills.
-
C.
Gevinson
Gevinson is the surname of Tavi Gevinson, an American writer, actress, and founder of the online magazine Rookie.
-
D.
Berlaymont girls’ school
Berlaymont girls’ school is a historic Catholic educational institution for girls established and run by the Ladies of Berlaymont congregation in Belgium.
-
E.
Harrow on the Hill
Harrow on the Hill is a historic village and suburban area in northwest London, known for its elevated position, picturesque streets, and the prestigious Harrow School.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e227fcf058819099d5ff965cc2c267 |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ed55a7c8190b4bc8bc325a5da5b |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:03 a.m.