Triple
T8690347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lais Ribeiro |
E206270
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lais Ribeiro |
E206270
|
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: Lais Ribeiro | Statement: [Lais Ribeiro, name, Lais Ribeiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lais Ribeiro Context triple: [Lais Ribeiro, name, Lais Ribeiro]
-
A.
Lais Ribeiro
chosen
Lais Ribeiro is a Brazilian fashion model best known for her work with Victoria’s Secret and appearances in its high-profile runway shows.
-
B.
Regina Silveira
Regina Silveira is a Brazilian contemporary artist renowned for her conceptual installations and explorations of shadow, perspective, and spatial perception.
-
C.
Sara Sampaio
Sara Sampaio is a Portuguese fashion model best known for her work with Victoria’s Secret and appearances in major international fashion magazines and campaigns.
-
D.
Camila Alves
Camila Alves is a Brazilian-American model, designer, and television host known for her fashion ventures and marriage to actor Matthew McConaughey.
-
E.
Fernanda Tadeu
Fernanda Tadeu is a Portuguese educator and public figure best known as the wife of former Prime Minister António Costa.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5734602c81909a0687e00f4a4a26 |
completed | March 31, 2026, 11:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3df73b88190b67138ee5129de8b |
completed | April 2, 2026, 10:55 p.m. |
Created at: March 30, 2026, 6:33 p.m.