Triple
T4642861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brown |
E101694
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Brun |
E419503
|
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: Brun | Statement: [Brown, hasVariant, Brun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brun Context triple: [Brown, hasVariant, Brun]
-
A.
Brun
chosen
Brun is a given name and surname of Germanic origin, closely related to and often used as a variant of Bruno.
-
B.
Bron
Bron is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
-
C.
Brandon
Brandon is a town in Suffolk, England, known for its location on the Breckland railway line and its surrounding Breckland heathland and forestry.
-
D.
Brandon
Brandon is a masculine given name of Old English origin meaning "hill covered with broom" or "beacon hill."
-
E.
Bern
Bern is the capital city of Switzerland, known for its well-preserved medieval old town and role as a political and cultural center.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a93047c8190990c94fd5a57c867 |
completed | March 20, 2026, 2:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfad80f14819097e022c9d9da17eb |
completed | March 21, 2026, 1:56 a.m. |
Created at: March 20, 2026, 1:14 p.m.