Triple
T754910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Curie |
E15532
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Maria
Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
|
E102694
|
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: Maria | Statement: [Marie Curie, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Marie Curie, givenName, Maria]
-
A.
Maria
Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
-
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, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
-
D.
Mary
Mary is the given first name of the acclaimed American actress Meryl Streep.
-
E.
Mary
Mary is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
- 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: Maria Triple: [Marie Curie, givenName, Maria]
Generated description
Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Target entity description: Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
-
A.
Maria
Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
-
B.
Mary
Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
-
C.
Mary
Mary is the given first name of the acclaimed American actress Meryl Streep.
-
D.
Mary
Mary is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
-
E.
Mary
Mary Eleanor Darwin was a member of the Darwin family, known primarily as a descendant of the naturalist Charles Darwin.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3aacc788190b79623c86b2a5fe7 |
completed | March 4, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69a7a5f0f5e08190b6eed2d8ca594cea |
completed | March 4, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7a64ee7e08190907a9e28994cc4d2 |
completed | March 4, 2026, 3:26 a.m. |
Created at: March 1, 2026, 7:37 p.m.