Triple
T3809850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria White Lowell |
E93104
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Maria
Maria is a feminine given name of Latin origin, historically associated with the Virgin Mary and widely used across many cultures and languages.
|
E103006
|
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: [Maria White Lowell, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria White Lowell, 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.
Maria
Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
-
C.
Maria
Maria is the young Puerto Rican woman at the heart of the musical "West Side Story," whose forbidden romance with Tony drives the story’s modern retelling of "Romeo and Juliet."
-
D.
Maria
Maria is the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
-
E.
Maria
Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
- 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: [Maria White Lowell, givenName, Maria]
Generated description
Maria is a feminine given name of Latin origin, historically associated with the Virgin Mary and widely used across many cultures and languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Target entity description: Maria is a feminine given name of Latin origin, historically associated with the Virgin Mary and widely used across many cultures and languages.
-
A.
Maria
chosen
Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
-
B.
Maria
Maria is an alternate given name of Letizia Ramolino, the mother of Napoleon Bonaparte and a notable figure in Corsican and French history.
-
C.
Maria
Maria is the birth name of Marie Curie, the pioneering physicist and chemist who conducted groundbreaking research on radioactivity.
-
D.
Maria
Maria is the middle given name of Cesare Maria De Vecchi, an Italian Fascist politician and prominent figure in Mussolini’s regime.
-
E.
Maria
Maria was a late Roman noblewoman of the Western Roman Empire, known primarily as the daughter of the powerful general Stilicho and wife of Emperor Honorius.
- 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_69aed96a60088190ab1df8390fffc935 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aee80e178081908cff71223bbf6c43 |
completed | March 9, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb33db9c81908b462ee80aaaad34 |
completed | March 14, 2026, 6:07 a.m. |
| NEDg | Description generation | batch_69b4fc08d65081908953482b10fa5611 |
completed | March 14, 2026, 6:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4fc7d8cf081909c4447818b5363c5 |
completed | March 14, 2026, 6:13 a.m. |
Created at: March 9, 2026, 3:16 p.m.