Triple
T11604611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Marie Anne de Bourbon |
E275221
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Anne
Anne is a French royal given name borne by Louise Marie Anne de Bourbon, an illegitimate daughter of King Louis XIV of France.
|
E938041
|
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: Anne | Statement: [Louise Marie Anne de Bourbon, givenName, Anne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Context triple: [Louise Marie Anne de Bourbon, givenName, Anne]
-
A.
Anne
Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
-
B.
Anne
Anne was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
-
C.
Anne
Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
-
D.
Anne
Anne is one of the central child protagonists in Enid Blyton’s Famous Five adventure series, known for her kindness, domestic sense, and cautious nature.
-
E.
Anne
Anne is one of the child protagonists in Enid Blyton’s Famous Five series, known for her cautious nature and love of home comforts during the group’s adventures.
- 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: Anne Triple: [Louise Marie Anne de Bourbon, givenName, Anne]
Generated description
Anne is a French royal given name borne by Louise Marie Anne de Bourbon, an illegitimate daughter of King Louis XIV of France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anne Target entity description: Anne is a French royal given name borne by Louise Marie Anne de Bourbon, an illegitimate daughter of King Louis XIV of France.
-
A.
Anne
Anne is the given name of Anne Hilarion de Costentin de Tourville, a renowned French naval commander of the late 17th and early 18th centuries.
-
B.
Anne
Anne is a female given name of Hebrew origin, commonly used in many European languages and historically borne by numerous queens, saints, and notable women.
-
C.
Anne
Anne was a Polish queen consort of the early 17th century, known as the wife of King Sigismund III Vasa and a member of the Habsburg dynasty.
-
D.
Anne
Anne is the given name of Anne Morrow Lindbergh, the American author and aviator who was married to famed aviator Charles Lindbergh.
-
E.
Anne
Anne is the birth name of Nancy Reagan, the former First Lady of the United States and wife of President Ronald Reagan.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d895502e0081909ee9c3d45d26cd91 |
completed | April 10, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee86f246848190a5b020c3e05d02dd |
completed | April 26, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_69eeb310e04c8190a1004662d5bbc015 |
completed | April 27, 2026, 12:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69eee95dfff48190a3c3022cdfc6dafc |
completed | April 27, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:38 p.m.