Triple
T13515047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ticha Penicheiro |
E322737
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ticha Penicheiro |
E322737
|
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: Ticha Penicheiro | Statement: [Ticha Penicheiro, name, Ticha Penicheiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ticha Penicheiro Context triple: [Ticha Penicheiro, name, Ticha Penicheiro]
-
A.
Ticha Penicheiro
chosen
Ticha Penicheiro is a Portuguese former professional basketball player and WNBA star renowned as one of the greatest passers and playmakers in women’s basketball history.
-
B.
Amada Cruz
Amada Cruz is an American museum director and arts administrator known for leading major art institutions, including serving as director of the Seattle Art Museum.
-
C.
Paz Ferreira
Paz Ferreira is the wife of retired Uruguayan football star Diego Forlán.
-
D.
Elisa Claro
Elisa Claro was the wife of French writer and Surrealist movement founder André Breton.
-
E.
Yolanda Penteado
Yolanda Penteado was a prominent Brazilian arts patron and cultural organizer who played a key role in the development of modern art in São Paulo.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d91e35881909a7184be0ad70c14 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:44 p.m.