Triple
T8451647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barrett |
E199811
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Barret |
E548052
|
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: Barret | Statement: [Barrett, hasVariant, Barret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barret Context triple: [Barrett, hasVariant, Barret]
-
A.
Barret
chosen
Barret is the middle name of William B. Travis, the 19th-century American lawyer and commander who became a key figure in the Battle of the Alamo during the Texas Revolution.
-
B.
Barrett
Barrett is a common English and Irish surname borne by numerous notable individuals across politics, law, sports, and the arts.
-
C.
Barret Zoph
Barret Zoph is a machine learning researcher known for his work on neural architecture search and contributions to deep learning at Google Brain.
-
D.
Barret Swatek
Barret Swatek is an American actress known for her roles in television series such as "10 Things I Hate About You," "Awkward," and "Yellowstone."
-
E.
Rennie
Rennie is a Scottish surname most notably associated with the family of civil engineers, including John Rennie the Younger.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44815488190a912d63512e19af0 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf512d294c8190bed7e37991d237c1 |
completed | April 3, 2026, 5:33 a.m. |
Created at: March 30, 2026, 6:09 p.m.