Triple
T15843203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midland F1 Racing |
E384147
|
entity |
| Predicate | driver |
P268
|
FINISHED |
| Object | Tiago Monteiro |
E384150
|
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: Tiago Monteiro | Statement: [Midland F1 Racing, driver, Tiago Monteiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiago Monteiro Context triple: [Midland F1 Racing, driver, Tiago Monteiro]
-
A.
Tiago Monteiro
chosen
Tiago Monteiro is a Portuguese racing driver best known for his Formula One career in the mid-2000s and later success in touring car championships.
-
B.
Tiago Nunes
Tiago Nunes is a Brazilian football manager known for coaching clubs such as Athletico Paranaense and Corinthians.
-
C.
Tiago Chaves
Tiago Chaves is an individual notable enough to be recognized as a prominent bearer of the surname Chaves.
-
D.
Tiago Tavares
Tiago Tavares is a Brazilian mixed martial artist known for competing in the lightweight division of major promotions such as the UFC.
-
E.
Diogo Tavares
Diogo Tavares is a Portuguese professional footballer known for playing as a forward for various clubs in Portugal and abroad.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142ea3da08190a9d2d5917f84907c |
completed | April 16, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa1412c9481909808473e14058033 |
completed | May 9, 2026, 9:04 p.m. |
Created at: April 10, 2026, 4:50 a.m.