Triple
T15263160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luis Aparicio |
E364835
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Luis |
E952830
|
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: Luis | Statement: [Luis Aparicio, givenName, Luis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luis Context triple: [Luis Aparicio, givenName, Luis]
-
A.
Luis
Luis is a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
-
B.
Luis
Luis is a comedic supporting character in the Marvel Cinematic Universe, best known as Scott Lang’s fast-talking friend and former cellmate in the Ant-Man films.
-
C.
Luis
Luis de Velasco y Aragón was a Spanish nobleman and colonial administrator who served as Viceroy of New Spain and later of Peru in the late 17th and early 18th centuries.
-
D.
Luis
Luis was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
-
E.
Luis
chosen
Luis is a common Spanish given name derived from the Germanic name Ludwig, widely used across Spanish-speaking countries.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084fed0481908e452c89cba2be82 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d3cf84c8190a4655803b12c9721 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:14 a.m.