Triple
T5791523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Journey to Italy |
E128404
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Maria Mauban
Maria Mauban was a French actress known for her roles in European cinema of the 1940s and 1950s, including notable performances in Italian neorealist and French films.
|
E551257
|
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: Maria Mauban | Statement: [Journey to Italy, stars, Maria Mauban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Mauban Context triple: [Journey to Italy, stars, Maria Mauban]
-
A.
Juanita Vanoy
Juanita Vanoy is a former model and Chicago-based real estate professional best known as the ex-wife of basketball legend Michael Jordan.
-
B.
Marlene Mathias
Marlene Mathias is known as the daughter of American Olympic decathlon champion and politician Bob Mathias.
-
C.
Jacqueline Cambas
Jacqueline Cambas is a film editor known for her work on the movie "Now and Then."
-
D.
Marjorie Estiano
Marjorie Estiano is a Brazilian actress and singer acclaimed for her powerful television performances and international recognition.
-
E.
Camile Velasco
Camile Velasco is a Filipino-American singer who gained national recognition as a finalist on the third season of the television talent show American Idol.
- 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: Maria Mauban Triple: [Journey to Italy, stars, Maria Mauban]
Generated description
Maria Mauban was a French actress known for her roles in European cinema of the 1940s and 1950s, including notable performances in Italian neorealist and French films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Mauban Target entity description: Maria Mauban was a French actress known for her roles in European cinema of the 1940s and 1950s, including notable performances in Italian neorealist and French films.
-
A.
Juanita Vanoy
Juanita Vanoy is a former model and Chicago-based real estate professional best known as the ex-wife of basketball legend Michael Jordan.
-
B.
Marlene Mathias
Marlene Mathias is known as the daughter of American Olympic decathlon champion and politician Bob Mathias.
-
C.
Jacqueline Cambas
Jacqueline Cambas is a film editor known for her work on the movie "Now and Then."
-
D.
Marjorie Estiano
Marjorie Estiano is a Brazilian actress and singer acclaimed for her powerful television performances and international recognition.
-
E.
Camile Velasco
Camile Velasco is a Filipino-American singer who gained national recognition as a finalist on the third season of the television talent show American Idol.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a56c73c81908a1c72c86e474b54 |
completed | March 22, 2026, 5:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a178ccf481909beddf56b66a588d |
completed | March 23, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69c0a2463cb08190aa5976ebd62c30d6 |
completed | March 23, 2026, 2:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a2afcef88190a77c8089a1b85393 |
completed | March 23, 2026, 2:17 a.m. |
Created at: March 22, 2026, 3:51 p.m.