Triple
T9821259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eure-et-Loir |
E238535
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lucé
Lucé is a suburban commune in northern France, located near the city of Chartres in the Eure-et-Loir department.
|
E823876
|
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: Lucé | Statement: [Eure-et-Loir, contains, Lucé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucé Context triple: [Eure-et-Loir, contains, Lucé]
-
A.
Armande
Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
-
B.
Béatrix
Béatrix is a novel by Honoré de Balzac that forms part of his larger La Comédie humaine cycle, depicting the complexities of love and society in 19th-century France.
-
C.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
D.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
E.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
- 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: Lucé Triple: [Eure-et-Loir, contains, Lucé]
Generated description
Lucé is a suburban commune in northern France, located near the city of Chartres in the Eure-et-Loir department.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lucé Target entity description: Lucé is a suburban commune in northern France, located near the city of Chartres in the Eure-et-Loir department.
-
A.
Armande
Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
-
B.
Béatrix
Béatrix is a novel by Honoré de Balzac that forms part of his larger La Comédie humaine cycle, depicting the complexities of love and society in 19th-century France.
-
C.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
D.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
E.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3147ecc81908cfca84c05a367d9 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc78ffcc8190bb26a224350376dc |
completed | April 5, 2026, 2:44 a.m. |
| NEDg | Description generation | batch_69d1cd8e7c548190bc3f10004db80925 |
completed | April 5, 2026, 2:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ce1aead081908da4a85ded350c17 |
completed | April 5, 2026, 2:51 a.m. |
Created at: March 30, 2026, 8:31 p.m.