Triple
T8126144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary of Guelders |
E189734
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mary
Mary of Guelders was a 15th-century duchess who became Queen consort of Scotland as the wife of King James II.
|
E713798
|
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: Mary | Statement: [Mary of Guelders, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary of Guelders, givenName, Mary]
-
A.
Mary
Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
-
B.
Mary
Mary is the middle name of Theresa May, the former Prime Minister of the United Kingdom.
-
C.
Mary
Mary I of England was the 16th-century Queen of England and Ireland best known for her attempt to restore Roman Catholicism and for the Marian persecutions that earned her the nickname "Bloody Mary."
-
D.
Mary
Mary is a studio album by Ghanaian rapper Sarkodie, known for its highlife influences and tribute to his late grandmother.
-
E.
Mary
Mary Allerton was a Mayflower passenger and one of the early settlers of Plymouth Colony in 17th-century New England.
- 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: Mary Triple: [Mary of Guelders, givenName, Mary]
Generated description
Mary of Guelders was a 15th-century duchess who became Queen consort of Scotland as the wife of King James II.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary of Guelders was a 15th-century duchess who became Queen consort of Scotland as the wife of King James II.
-
A.
Mary
Mary was a 16th-century Habsburg archduchess who became Queen consort of Hungary and Bohemia through her marriage to King Louis II.
-
B.
Mary
Mary of York was a 15th-century English princess, the second daughter of King Edward IV and Elizabeth Woodville.
-
C.
Mary
Mary of Burgundy, Duchess of Savoy, was a 15th-century noblewoman from the influential Burgundian dynasty who became Duchess consort of Savoy through marriage.
-
D.
Mary
Mary, Princess Royal and Princess of Orange, was the eldest daughter of King Charles I of England and the wife of William II of Orange, making her a key figure in 17th-century Anglo-Dutch royal relations.
-
E.
Mary
Mary II of England was a late 17th-century Queen of England, Scotland, and Ireland who ruled jointly with her husband William III after the Glorious Revolution.
- 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_69ca82bb74848190afb1f18640632c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb438eb778819085296e6cbfa2e70d |
completed | March 31, 2026, 3:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc946b44d08190a042932ee908dc2f |
completed | April 1, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69cc95c0b19881908521cce5ac0fe197 |
completed | April 1, 2026, 3:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc970698f88190a0869515904e50e3 |
completed | April 1, 2026, 3:54 a.m. |
Created at: March 30, 2026, 5:34 p.m.