Triple
T18256340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberto Ierusalimschy |
E437230
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Waldemar Celes |
—
|
NE NERFINISHED |
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: Waldemar Celes | Statement: [Roberto Ierusalimschy, collaboratedWith, Waldemar Celes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldemar Celes Context triple: [Roberto Ierusalimschy, collaboratedWith, Waldemar Celes]
-
A.
Waldemar Celes
chosen
Waldemar Celes is a Brazilian computer scientist and software engineer best known as one of the principal designers of the Lua programming language.
-
B.
Jorge Taiana
Jorge Taiana is an Argentine politician and diplomat who has served as the country’s foreign minister and held various prominent roles in national and international affairs.
-
C.
Fernando Wagner
Fernando Wagner was a German-born Mexican character actor and director known for his supporting roles in mid-20th-century Mexican cinema.
-
D.
Tadeu
Tadeu is a given name, primarily used in Portuguese-speaking countries, that is a variant of the name Tadeusz.
-
E.
Tadeu Marroco
Tadeu Marroco is a Brazilian-born business executive who serves as the chief executive officer of British American Tobacco.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd85ee548190a102611fcf709ad4 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:34 a.m.