Triple
T6811012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lúcio Costa |
E156632
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Costa |
E111284
|
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: Costa | Statement: [Lúcio Costa, familyName, Costa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Costa Context triple: [Lúcio Costa, familyName, Costa]
-
A.
Costa
chosen
Costa is a common Portuguese surname borne by numerous notable figures in politics, sports, and the arts.
-
B.
Costa
Costa is a Chilean wine-producing subregion within the Cachapoal Valley, known for its coastal influence that shapes the style and character of its wines.
-
C.
Costa Cálida
Costa Cálida is a popular coastal region in southeastern Spain known for its warm climate, sandy beaches, and seaside resorts along the Mediterranean.
-
D.
Costa Esmeralda
Costa Esmeralda is a scenic coastal tourist region in eastern Mexico known for its long stretches of sandy beaches, warm Gulf waters, and relaxed resort atmosphere.
-
E.
Costa Sur
Costa Sur is a coastal region in the Mexican state of Jalisco known for its Pacific beaches, fishing villages, and tourism.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30ded6481908fd64611607c610e |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723d775a48190bfdf5b6a52339833 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:16 p.m.