Triple
T17521548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thiago Teixeira |
E426688
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Thiago Teixeira |
—
|
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: Thiago Teixeira | Statement: [Thiago Teixeira, name, Thiago Teixeira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thiago Teixeira Context triple: [Thiago Teixeira, name, Thiago Teixeira]
-
A.
Thiago Teixeira
chosen
Thiago Teixeira is a technology entrepreneur best known as a co-founder of the data app development platform Streamlit.
-
B.
Thiago Soares
Thiago Soares is a renowned Brazilian ballet dancer best known as a former principal dancer of The Royal Ballet in London.
-
C.
Leandro Barbosa
Leandro Barbosa is a Brazilian professional basketball player and NBA champion known for his speed and scoring ability, particularly during his tenure with the Phoenix Suns.
-
D.
Rodrigo Teixeira
Rodrigo Teixeira is a Brazilian film producer known for backing acclaimed independent and international films such as "Armageddon Time," "Call Me by Your Name," and "The Witch."
-
E.
Leandro Nunes
Leandro Nunes is a Brazilian jiu-jitsu black belt competitor and coach known within the grappling community for his technical skill and tournament performances.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d2f79881909556894728e255ab |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.