Triple
T3092113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgiana Byng |
E64504
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Byng |
E228229
|
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: Byng | Statement: [Georgiana Byng, familyName, Byng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Byng Context triple: [Georgiana Byng, familyName, Byng]
-
A.
Byng
chosen
Byng is an English surname most notably associated with Julian Byng, a British Army officer and World War I general who later served as Governor General of Canada.
-
B.
Bordon
Bordon is a town in East Hampshire, England, historically known for its large army camp and military training facilities.
-
C.
Brylin
Brylin is the surname of Sergei Brylin, a former Russian professional ice hockey player and three-time Stanley Cup champion with the New Jersey Devils.
-
D.
Hayes
Hayes is a suburban town in west London, England, known for its residential areas, transport links, and proximity to Heathrow Airport.
-
E.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada21055b88190b602425a513af7e6 |
completed | March 8, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b203697abc8190b93e8c85ada5bdfc |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.