Triple
T12835370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luis Tiant |
E306896
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Luis
Luis is the given name of Luis Tiant, a renowned Cuban former Major League Baseball pitcher known for his distinctive delivery and success with the Boston Red Sox.
|
E952830
|
NE FINISHED |
How this triple was built (4 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 Tiant, givenName, Luis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luis Context triple: [Luis Tiant, 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 the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
-
C.
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.
-
D.
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.
-
E.
Luis
Luis was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Luis Triple: [Luis Tiant, givenName, Luis]
Generated description
Luis is the given name of Luis Tiant, a renowned Cuban former Major League Baseball pitcher known for his distinctive delivery and success with the Boston Red Sox.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luis Target entity description: Luis is the given name of Luis Tiant, a renowned Cuban former Major League Baseball pitcher known for his distinctive delivery and success with the Boston Red Sox.
-
A.
Luis
Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
-
B.
Luis
chosen
Luis is a common Spanish given name derived from the Germanic name Ludwig, widely used across Spanish-speaking countries.
-
C.
Luis
Luis is a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
-
D.
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.
-
E.
Luis
Luis was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
- F. None of above.
Provenance (5 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96fb1c7248190bb6e644e041d192e |
completed | April 10, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73051273c81909eb91c923f37557e |
completed | May 3, 2026, 11:24 a.m. |
| NEDg | Description generation | batch_69f73195e4d88190ad356d0e3e18d34f |
completed | May 3, 2026, 11:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73220ffc08190bfb1b89757efd606 |
completed | May 3, 2026, 11:31 a.m. |
Created at: April 9, 2026, 5:34 p.m.