Triple
T15537601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamie |
E370389
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object |
Mary
Mary is a traditional and widely used female given name with deep historical and religious significance in many cultures.
|
E75782
|
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: [Mamie, hasRelatedName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mamie, hasRelatedName, Mary]
-
A.
Mary
Mary is a significant urban and economic center in southeastern Turkmenistan, known for its role in the country’s natural gas and cotton industries.
-
B.
Mary
Mary is the central, titular figure evoked in Jimi Hendrix’s song “The Wind Cries Mary,” often interpreted as a symbol of lost love and melancholy.
-
C.
Mary
Mary is a central character in Ralph Vaughan Williams's opera "Hugh the Drover," serving as the romantic interest whose choices drive much of the plot.
-
D.
Mary
Mary is the given name of Mary Elizabeth Baird Bryan, an American figure known primarily in relation to her husband, politician William Jennings Bryan.
-
E.
Mary
Mary is the first name of American film actress Peggy Moran, who appeared in numerous Hollywood movies during the late 1930s and early 1940s.
- 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: [Mamie, hasRelatedName, Mary]
Generated description
Mary is a traditional and widely used female given name with deep historical and religious significance in many cultures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Target entity description: Mary is a traditional and widely used female given name with deep historical and religious significance in many cultures.
-
A.
Mary
chosen
Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
-
B.
Mary
Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
-
C.
Mary
Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
-
D.
Mary
Mary is the given name of Mary Sidney, an English Renaissance noblewoman, writer, and literary patron.
-
E.
Mary
Mary is the given name of Mary Cassatt, the renowned American Impressionist painter known for her depictions of women and children.
- F. None of above.
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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442f3c688190a599165e526af2ed |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c39ffbc819089cea285e8145fa4 |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff4ccbd1048190b7f40ede90da7640 |
completed | May 9, 2026, 3:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff4d4033348190a209029d3d2f207b |
completed | May 9, 2026, 3:05 p.m. |
Created at: April 10, 2026, 4:06 a.m.