Triple
T10253906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Barrett |
E240412
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Barrett |
E199811
|
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: Barrett | Statement: [Scott Barrett, familyName, Barrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barrett Context triple: [Scott Barrett, familyName, Barrett]
-
A.
Barrett
chosen
Barrett is a common English and Irish surname borne by numerous notable individuals across politics, law, sports, and the arts.
-
B.
Barret
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.
-
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.
Barnett
Barnett is an English-language surname of Norman origin that has been borne by various notable figures in fields such as politics, academia, and the arts.
-
E.
Barnett
Barnett is a masculine given name most notably associated with the influential American abstract expressionist painter Barnett Newman.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24b9a308190bba6d8e3e22e5ee0 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7cec62c819083e493e0fc7c65b5 |
completed | April 9, 2026, 12:50 a.m. |
Created at: April 6, 2026, 11:29 a.m.