Triple
T20202008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Belasyse |
E493244
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Belasyse |
—
|
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: Belasyse | Statement: [John Belasyse, familyName, Belasyse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belasyse Context triple: [John Belasyse, familyName, Belasyse]
-
A.
Belasyse
chosen
Belasyse is an English noble family name historically associated with aristocratic titles such as the Earls Fauconberg.
-
B.
de Belmeis
de Belmeis is a medieval Anglo-Norman family name associated with prominent clerics and officials in the English church and royal administration.
-
C.
Bollaert
Bollaert is the commonly used nickname for Stade Bollaert-Delelis, the historic football stadium in Lens, France.
-
D.
Breuillet
Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
-
E.
Mistinguett
Mistinguett was a famous French actress and singer of the early 20th century, celebrated as one of Paris’s most iconic music-hall stars.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d8e0df481909c030e2a01d1862a |
completed | April 20, 2026, 6:16 p.m. |
Created at: April 11, 2026, 11:37 p.m.