Triple
T20492972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuando seas mía |
E502793
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Iliana Fox
Iliana Fox is a Mexican actress known for her work in telenovelas, film, and television.
|
E1434781
|
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: Iliana Fox | Statement: [Cuando seas mía, castMember, Iliana Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iliana Fox Context triple: [Cuando seas mía, castMember, Iliana Fox]
-
A.
Chiara Fox
Chiara Fox is a user experience and information architecture professional known for co-founding the influential UX consultancy Adaptive Path.
-
B.
Jorja-An Fox
Jorja-An Fox is an American actress and producer best known for her roles on the television series "ER" and "CSI: Crime Scene Investigation."
-
C.
Leilani Sarelle
Leilani Sarelle is an American actress best known for her role as Roxy in the 1992 thriller film "Basic Instinct."
-
D.
Roxeanne Avent
Roxeanne Avent is an American film producer and entertainment executive known for her work on independent and faith-based movies.
-
E.
Alixandra Fazzina
Alixandra Fazzina is a British photojournalist renowned for her powerful documentation of refugees, conflict, and humanitarian crises around the world.
- 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: Iliana Fox Triple: [Cuando seas mía, castMember, Iliana Fox]
Generated description
Iliana Fox is a Mexican actress known for her work in telenovelas, film, and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Iliana Fox Target entity description: Iliana Fox is a Mexican actress known for her work in telenovelas, film, and television.
-
A.
Chiara Fox
Chiara Fox is a user experience and information architecture professional known for co-founding the influential UX consultancy Adaptive Path.
-
B.
Jorja-An Fox
Jorja-An Fox is an American actress and producer best known for her roles on the television series "ER" and "CSI: Crime Scene Investigation."
-
C.
Leilani Sarelle
Leilani Sarelle is an American actress best known for her role as Roxy in the 1992 thriller film "Basic Instinct."
-
D.
Roxeanne Avent
Roxeanne Avent is an American film producer and entertainment executive known for her work on independent and faith-based movies.
-
E.
Alixandra Fazzina
Alixandra Fazzina is a British photojournalist renowned for her powerful documentation of refugees, conflict, and humanitarian crises around the world.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbb3bd081909351525208b41bba |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0893b8a86081908783a9b8cf2dc485 |
completed | May 16, 2026, 3:56 p.m. |
| NEDg | Description generation | batch_6a08962f4e3881908df0bb55b6239c86 |
completed | May 16, 2026, 4:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0896b417bc8190963b69f84ea0e3c8 |
completed | May 16, 2026, 4:09 p.m. |
Created at: April 16, 2026, 11:35 a.m.