Triple
T22163634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alicia Sierra |
E547732
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Germán |
—
|
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: Germán | Statement: [Alicia Sierra, spouse, Germán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Germán Context triple: [Alicia Sierra, spouse, Germán]
-
A.
Germán
chosen
Germán is a Spanish given name, commonly used in Spanish-speaking countries and derived from the same roots as the name Germain.
-
B.
Alemão
Alemão is a former Brazilian midfielder best known for his influential role at Napoli in the late 1980s and early 1990s, where he helped the club achieve major European and domestic success.
-
C.
Germann
Germann is a surname most notably associated with American actor Greg Germann, known for his roles in television and film.
-
D.
Germano
Germano is a masculine given name and surname of Romance-language origin, cognate with the French name Germain.
-
E.
Parlatino
Parlatino is a regional parliamentary organization that brings together the legislative bodies of Latin American countries to promote political integration, democracy, and cooperation across the region.
- 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2f2f90819080b5bb73a6052c24 |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.