Triple
T31530703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Octobre |
E804469
|
entity |
| Predicate | characterPlayedBy_Serge Reggiani |
P197300
|
FINISHED |
| Object |
Antoine
Antoine is a fictional character portrayed by French actor Serge Reggiani in the 1959 French thriller film "Marie-Octobre."
|
E1978802
|
NE FINISHED |
How this triple was built (3 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: Antoine | Statement: [Marie-Octobre, characterPlayedBy_Serge Reggiani, Antoine]
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: Antoine Triple: [Marie-Octobre, characterPlayedBy_Serge Reggiani, Antoine]
Generated description
Antoine is a fictional character portrayed by French actor Serge Reggiani in the 1959 French thriller film "Marie-Octobre."
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy_Serge Reggiani Context triple: [Marie-Octobre, characterPlayedBy_Serge Reggiani, Antoine]
-
A.
characterPlayedBy_Lino Ventura
Indicates that a given character is portrayed or acted by Lino Ventura.
-
B.
leadActorForCharacter Detective Richard Capparelli
Indicates that the specified person is the primary actor portraying the character Detective Richard Capparelli.
-
C.
leadActorForCharacter Detective Sandy Calloway
Indicates that the specified person is the primary actor portraying the character Detective Sandy Calloway.
-
D.
characterPlayedBy_Charles Bronson
Indicates that a given character is portrayed or acted by Charles Bronson.
-
E.
roleOfDellaStreetPlayedBy
Indicates that a specified actor portrays the character Della Street in a performance or production.
- F. None of above. chosen
Provenance (7 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2d9d3598c48190879800dedc6f843f |
completed | June 13, 2026, 6:11 p.m. |
| NEDg | Description generation | batch_6a2da3de320c81908b08438c76226569 |
completed | June 13, 2026, 6:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2da5584fcc8190859f3c0278975a9d |
completed | June 13, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
| PDg | Predicate description generation | batch_69fe86c98d688190a99d5dcb14e2dc95 |
completed | May 9, 2026, 12:58 a.m. |
Created at: April 30, 2026, 10:01 p.m.