Triple
T1978480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Un Chien Andalou |
E42969
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Fano Messan
Fano Messan was a French actress active in early 20th-century cinema, known for appearing in avant-garde and silent films.
|
E223581
|
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: Fano Messan | Statement: [Un Chien Andalou, castMember, Fano Messan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fano Messan Context triple: [Un Chien Andalou, castMember, Fano Messan]
-
A.
Giovanni Messe
Giovanni Messe was an Italian general and later Marshal of Italy, noted for his leadership in World War II and subsequent role as a postwar political figure.
-
B.
Pietro Gazzera
Pietro Gazzera was an Italian general and colonial governor best known for his leadership of Italian forces in East Africa during World War II.
-
C.
Giovanni Molari
Giovanni Molari is an Italian academic and engineer who serves as rector of the historic University of Bologna.
-
D.
Lino Lacedelli
Lino Lacedelli was an Italian mountaineer best known for being one of the first climbers to reach the summit of K2 in 1954.
-
E.
Enrico Barra
Enrico Barra is an individual notable for bearing the surname Barra, though specific widely recognized biographical details about him are not well documented.
- 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: Fano Messan Triple: [Un Chien Andalou, castMember, Fano Messan]
Generated description
Fano Messan was a French actress active in early 20th-century cinema, known for appearing in avant-garde and silent films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fano Messan Target entity description: Fano Messan was a French actress active in early 20th-century cinema, known for appearing in avant-garde and silent films.
-
A.
Giovanni Messe
Giovanni Messe was an Italian general and later Marshal of Italy, noted for his leadership in World War II and subsequent role as a postwar political figure.
-
B.
Pietro Gazzera
Pietro Gazzera was an Italian general and colonial governor best known for his leadership of Italian forces in East Africa during World War II.
-
C.
Giovanni Molari
Giovanni Molari is an Italian academic and engineer who serves as rector of the historic University of Bologna.
-
D.
Lino Lacedelli
Lino Lacedelli was an Italian mountaineer best known for being one of the first climbers to reach the summit of K2 in 1954.
-
E.
Enrico Barra
Enrico Barra is an individual notable for bearing the surname Barra, though specific widely recognized biographical details about him are not well documented.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb43011188190b6a41c004e9e4802 |
completed | March 7, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032988ec8190b9012cbb77e7efa4 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae03c4faac8190a13aa0882eda3629 |
completed | March 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0445a9608190918a7bd45b9bf999 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.