Triple
T1668315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brendan |
E36062
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Brendyn |
E188066
|
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: Brendyn | Statement: [Brendan, hasVariant, Brendyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brendyn Context triple: [Brendan, hasVariant, Brendyn]
-
A.
Brendon
chosen
Brendon is a given name, typically a variant spelling of Brendan, used for males in English-speaking countries.
-
B.
Reilly
Reilly is a surname most notably associated with William K. Reilly, an American environmentalist and former administrator of the U.S. Environmental Protection Agency.
-
C.
Myles
Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
-
D.
Brenna
Brenna is a Norwegian surname most notably borne by Tonje Brenna, a contemporary Norwegian politician.
-
E.
Dylan Highsmith
Dylan Highsmith is a film editor best known for his work on major action and science-fiction movies, including Pacific Rim: Uprising.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62d1261481909a01c8fe4ff7500d |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ac15c3c8190ba730217efd69a77 |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:29 p.m.