Triple
T6492524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand de Marsin |
E148075
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
de Marsin
De Marsin is a French noble family name historically associated with military and aristocratic figures such as Marshal Ferdinand de Marsin.
|
E595447
|
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: de Marsin | Statement: [Ferdinand de Marsin, familyName, de Marsin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de Marsin Context triple: [Ferdinand de Marsin, familyName, de Marsin]
-
A.
De Mornay
De Mornay is the surname of American actress Rebecca De Mornay, known for her roles in films such as "Risky Business" and "The Hand That Rocks the Cradle."
-
B.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
-
C.
Michel
Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
-
D.
Michel
Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
-
E.
Michel
Michel is a French given name commonly used for males, equivalent to "Michael" in English.
- 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: de Marsin Triple: [Ferdinand de Marsin, familyName, de Marsin]
Generated description
De Marsin is a French noble family name historically associated with military and aristocratic figures such as Marshal Ferdinand de Marsin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: de Marsin Target entity description: De Marsin is a French noble family name historically associated with military and aristocratic figures such as Marshal Ferdinand de Marsin.
-
A.
De Mornay
De Mornay is the surname of American actress Rebecca De Mornay, known for her roles in films such as "Risky Business" and "The Hand That Rocks the Cradle."
-
B.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
-
C.
Michel
Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
-
D.
Michel
Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
-
E.
Michel
Michel is a French given name commonly used for males, equivalent to "Michael" in English.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a9bf9208190b0957eda06ed3d65 |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653bf5c30819083e4e5484b2bd8cc |
completed | March 27, 2026, 9:54 a.m. |
| NEDg | Description generation | batch_69c6547160fc8190b64176073bf94cad |
completed | March 27, 2026, 9:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6553dcbe48190881c27f0ad095345 |
completed | March 27, 2026, 10 a.m. |
Created at: March 22, 2026, 4:53 p.m.