Triple
T11135382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovanni Battista Betancourt |
E263395
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Betancourt |
E415037
|
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: Betancourt | Statement: [Giovanni Battista Betancourt, familyName, Betancourt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betancourt Context triple: [Giovanni Battista Betancourt, familyName, Betancourt]
-
A.
Betancourt
chosen
Betancourt is a Spanish-language surname most notably associated with Rómulo Betancourt, a key figure in Venezuelan democratic politics.
-
B.
Billancourt
Billancourt is a Paris Métro station in Boulogne-Billancourt serving the western suburbs of the French capital.
-
C.
Boustany
Boustany is a surname of Lebanese origin notably associated with several prominent political and professional families, particularly in the United States and Lebanon.
-
D.
Massy
Massy is a suburban town in the southern outskirts of Paris, France, known as a significant transport hub with major RER and TGV connections.
-
E.
Avellaneda
Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e85daddc8190a1ae2a4a75cc8d50 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e441fa286881909a8279a8ea6944e7 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.