Triple
T1980514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annabella |
E43014
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Charpentier
Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
|
E225104
|
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: Charpentier | Statement: [Annabella, familyName, Charpentier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charpentier Context triple: [Annabella, familyName, Charpentier]
-
A.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
B.
Roussel
Roussel is a surname of French origin, often used as an alternative spelling of Russell.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
De La Motte
De La Motte is a French-origin surname historically associated with various notable figures, including early 20th-century American silent film actress Marguerite De La Motte.
-
E.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
- 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: Charpentier Triple: [Annabella, familyName, Charpentier]
Generated description
Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charpentier Target entity description: Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
-
A.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
B.
Roussel
Roussel is a surname of French origin, often used as an alternative spelling of Russell.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
De La Motte
De La Motte is a French-origin surname historically associated with various notable figures, including early 20th-century American silent film actress Marguerite De La Motte.
-
E.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb7c87bc081908ed179d1ca94fa3b |
completed | March 7, 2026, 5:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ad2a3888190a93e54b53a071afc |
completed | March 8, 2026, 11:48 p.m. |
| NEDg | Description generation | batch_69ae0b8bd2bc8190a6f16519f3f6e924 |
completed | March 8, 2026, 11:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0bf5364c8190bffbbd211a5e11a6 |
completed | March 8, 2026, 11:53 p.m. |
Created at: March 4, 2026, 7:37 p.m.