Triple
T12366408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bebel Gilberto |
E294879
|
entity |
| Predicate | hasDiscographyItem |
P1995
|
FINISHED |
| Object | Tudo |
E846201
|
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: Tudo | Statement: [Bebel Gilberto, hasDiscographyItem, Tudo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tudo Context triple: [Bebel Gilberto, hasDiscographyItem, Tudo]
-
A.
TUDO
TUDO is the commonly used abbreviation for TU Dortmund University, a technical university in Dortmund, Germany known for its engineering, natural sciences, and computer science programs.
-
B.
Tout
Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
-
C.
"Everything"
"Everything" is a romantic pop-jazz ballad by Canadian singer Michael Bublé, celebrated for its upbeat melody and heartfelt lyrics.
-
D.
Tudo Bem!
chosen
Tudo Bem! is a jazz album by guitarist Joe Pass that showcases his virtuosic playing in a Brazilian-influenced setting.
-
E.
ALL
ALL is the stock ticker symbol for Allstate Corporation, a major U.S. insurance company known primarily for its auto and home insurance products.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fa502988190ba170dee90d9f394 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63473efd481909b2061f3b19e1aaf |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.