Triple
T1777736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María Picasso y López |
E39218
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | López |
E197855
|
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: López | Statement: [María Picasso y López, familyName, López]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: López Context triple: [María Picasso y López, familyName, López]
-
A.
López
chosen
López is a common Spanish surname widely borne across Spain and Latin America.
-
B.
Sosa
Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
-
C.
Hernández
Hernández is a common Spanish surname borne by numerous notable figures across sports, arts, and public life.
-
D.
Gutiérrez
Gutiérrez is a common Spanish-language surname borne by numerous individuals across the Spanish-speaking world.
-
E.
Montero Ríos
Montero Ríos is the surname of Eugenio Montero Ríos, a prominent Spanish jurist and politician who served as Prime Minister of Spain in the early 20th century.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b967f08190a73216361b9c2d83 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c96694819085f3ccafb141802f |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:31 p.m.