Triple
T5845458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Barra |
E129697
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Barra |
E19261
|
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: Barra | Statement: [Francesco Barra, hasSurname, Barra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barra Context triple: [Francesco Barra, hasSurname, Barra]
-
A.
Barra
Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
-
B.
Barra
chosen
Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
-
C.
La Barra
La Barra is a popular seaside resort town in Uruguay known for its beaches, nightlife, and proximity to Punta del Este.
-
D.
De Barra
De Barra is a variant form of the name Barra, typically used as a surname or family name in Irish and Scottish contexts.
-
E.
Barras
Barras is a French surname most notably associated with Paul Barras, a leading political figure of the French Revolution and the Directory.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034dcafe88190a438034a539ffa52 |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0bfce88f88190bbc78ce9c7c3c107 |
completed | March 23, 2026, 4:21 a.m. |
Created at: March 22, 2026, 3:55 p.m.