Triple
T21477584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hortência Marcari |
E529902
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hortência |
—
|
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: Hortência | Statement: [Hortência Marcari, givenName, Hortência]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hortência Context triple: [Hortência Marcari, givenName, Hortência]
-
A.
Hortência
chosen
Hortência is a legendary Brazilian basketball player widely regarded as one of the greatest female players in the sport’s history.
-
B.
Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
-
C.
Sarraméa
Sarraméa is a small inland commune in New Caledonia known for its lush mountainous landscapes and eco-tourism activities.
-
D.
Morumbi
Morumbi is a major football stadium in São Paulo, Brazil, best known as the home ground of São Paulo FC and a frequent venue for major national and international matches.
-
E.
Jaqueira
Jaqueira is a neighborhood in Recife, Brazil, known for its large urban park and residential character.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1951fc8190910f634327aa5c3f |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:20 p.m.