Triple
T22401796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Carbonero |
E553778
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Sara
Sara is a Spanish sports journalist and television presenter best known for her work covering football and her high-profile public presence.
|
E1533993
|
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: Sara | Statement: [Sara Carbonero, givenName, Sara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Context triple: [Sara Carbonero, givenName, Sara]
-
A.
Sara
Sara is a language spoken in parts of Central Africa, particularly in Chad.
-
B.
Sara
"Sara" is a soft rock song by Fleetwood Mac, written and sung by Stevie Nicks, known for its dreamy lyrics and prominent place on their 1979 album *Tusk*.
-
C.
Sara
Sara is the imaginative and resilient young heroine of Frances Hodgson Burnett’s classic children’s novel "A Little Princess."
-
D.
Sara
Sara is the central protagonist of the film "Runaway Train," around whom the story’s dramatic events and emotional stakes revolve.
-
E.
Sara
Sara is the central female protagonist of the Italian film "L’uomo che ama," around whom the story’s emotional and relational conflicts revolve.
- 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: Sara Triple: [Sara Carbonero, givenName, Sara]
Generated description
Sara is a Spanish sports journalist and television presenter best known for her work covering football and her high-profile public presence.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sara Target entity description: Sara is a Spanish sports journalist and television presenter best known for her work covering football and her high-profile public presence.
-
A.
Sara
Sara is a television host and journalist best known as a co-host of the daytime talk show "The View."
-
B.
Sara
Sara is the first name of Sara Blakely, the American entrepreneur and founder of the shapewear company Spanx.
-
C.
Sara
Sara is the given name of the Irish stage and film actress Sara Allgood, known for her work in early 20th-century theatre and cinema.
-
D.
Sara
Sara is the given name of American actress and singer Sara Paxton, known for her roles in film and television.
-
E.
Sara
Sara is the given name of Sara Duterte, a prominent Filipino politician and former mayor of Davao City who has served as Vice President of the Philippines.
- F. None of above. chosen
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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b4a96c8190838f5dda21c4d853 |
completed | April 29, 2026, 1:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9cd35648190a37c9814c581749e |
completed | May 18, 2026, 10:28 a.m. |
| NEDg | Description generation | batch_6a0aea9aad5c81908fca5ea2b594effb |
completed | May 18, 2026, 10:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aeb5137c08190b5b787c85f239a67 |
completed | May 18, 2026, 10:34 a.m. |
Created at: April 16, 2026, 8:46 p.m.