Triple
T4049571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annecy |
E84150
|
entity |
| Predicate | mayor |
P185
|
FINISHED |
| Object |
François Astorg
François Astorg is a French politician who serves as the mayor of the city of Annecy in southeastern France.
|
E599142
|
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: François Astorg | Statement: [Annecy, mayor, François Astorg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: François Astorg Context triple: [Annecy, mayor, François Astorg]
-
A.
Léon Azéma
Léon Azéma was a 20th-century French architect known for major public works in Paris, including co-designing the Palais de Chaillot for the 1937 Exposition.
-
B.
Louis Méjan
Louis Méjan was a French political figure known for helping establish the centrist-liberal Democratic Republican Alliance in the early Third Republic.
-
C.
François Olivennes
François Olivennes is a French obstetrician and gynecologist specializing in reproductive medicine and fertility treatment.
-
D.
Georges Lacombe
Georges Lacombe was a French Post-Impressionist painter and sculptor associated with the Nabi group, known for his symbolist and decorative style.
-
E.
François Douaren
François Douaren was a 16th-century French jurist and humanist scholar known for his influential contributions to legal humanism and Roman law studies.
- 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: François Astorg Triple: [Annecy, mayor, François Astorg]
Generated description
François Astorg is a French politician who serves as the mayor of the city of Annecy in southeastern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: François Astorg Target entity description: François Astorg is a French politician who serves as the mayor of the city of Annecy in southeastern France.
-
A.
Léon Azéma
Léon Azéma was a 20th-century French architect known for major public works in Paris, including co-designing the Palais de Chaillot for the 1937 Exposition.
-
B.
Louis Méjan
Louis Méjan was a French political figure known for helping establish the centrist-liberal Democratic Republican Alliance in the early Third Republic.
-
C.
François Olivennes
François Olivennes is a French obstetrician and gynecologist specializing in reproductive medicine and fertility treatment.
-
D.
Georges Lacombe
Georges Lacombe was a French Post-Impressionist painter and sculptor associated with the Nabi group, known for his symbolist and decorative style.
-
E.
François Douaren
François Douaren was a 16th-century French jurist and humanist scholar known for his influential contributions to legal humanism and Roman law studies.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb82d1a08190aa8c5c48d368b58b |
completed | March 9, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cad46d4081908f685d961d100d42 |
completed | March 27, 2026, 6:22 p.m. |
| NEDg | Description generation | batch_69c6cc960e088190bd9643aa1c46128d |
completed | March 27, 2026, 6:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cd4d50948190ac60ec518f00e5d8 |
completed | March 27, 2026, 6:32 p.m. |
Created at: March 9, 2026, 3:37 p.m.