Triple
T6180581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Djanira |
E137931
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Djanira |
E137931
|
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: Djanira | Statement: [Djanira, name, Djanira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Djanira Context triple: [Djanira, name, Djanira]
-
A.
Djanira
chosen
Djanira was a prominent Brazilian modernist painter known for her vivid depictions of everyday life, religious themes, and popular culture.
-
B.
Tatjana
Tatjana is a feminine given name, commonly used in various European countries as a variant of Tatyana.
-
C.
Zinetula
Zinetula is a masculine given name most notably borne by Russian ice hockey coach and former player Zinetula Bilyaletdinov.
-
D.
Debinha
Debinha is a Brazilian professional footballer renowned as one of the top attacking midfielders/forwards in women’s soccer, starring for both the Brazil national team and in the National Women’s Soccer League.
-
E.
Renata
Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
- 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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c060fdf7ac8190a0e887907ec9a922 |
completed | March 22, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c141bf3f4081909849e38d322da251 |
completed | March 23, 2026, 1:35 p.m. |
Created at: March 22, 2026, 4:18 p.m.