Triple
T1334457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firmin Didot |
E28715
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
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.
|
E238077
|
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: Firmin | Statement: [Firmin Didot, givenName, Firmin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Firmin Context triple: [Firmin Didot, givenName, Firmin]
-
A.
Donatien
Donatien is the given name of Jean-Baptiste Donatien de Vimeur, comte de Rochambeau, a prominent French general who played a key role in the American Revolutionary War.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
-
D.
Louiguy
Louiguy was a French composer best known for co-writing the iconic chanson "La Vie en rose," popularized by Édith Piaf.
-
E.
Stephen Sauvestre
Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
- 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: Firmin Triple: [Firmin Didot, givenName, Firmin]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Firmin Target entity description: 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.
-
A.
Donatien
Donatien is the given name of Jean-Baptiste Donatien de Vimeur, comte de Rochambeau, a prominent French general who played a key role in the American Revolutionary War.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
-
D.
Louiguy
Louiguy was a French composer best known for co-writing the iconic chanson "La Vie en rose," popularized by Édith Piaf.
-
E.
Stephen Sauvestre
Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae515ce1b0819089603a3e0f6b1933 |
completed | March 9, 2026, 4:49 a.m. |
| NEDg | Description generation | batch_69ae553d38f4819081d00f6c6451f7ed |
completed | March 9, 2026, 5:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae55875b5081909cfe62b222d229f6 |
completed | March 9, 2026, 5:07 a.m. |
Created at: March 1, 2026, 7:55 p.m.