Triple
T13265759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Cooper Janis |
E315918
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Maria
Maria is a feminine given name of Latin origin, widely used in many cultures and often associated with the Christian tradition.
|
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 Cooper Janis, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria Cooper Janis, givenName, Maria]
-
A.
Maria
Maria is a track on Rage Against the Machine’s 2000 album "The Battle of Los Angeles," known for its politically charged lyrics and aggressive rap metal sound.
-
B.
Maria
Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
-
C.
Maria
Maria is a witty and sharp-tongued gentlewoman in Olivia’s household in Shakespeare’s comedy "Twelfth Night," known for her clever schemes and playful manipulation of other characters.
-
D.
Maria
Maria is a coastal municipality on Siquijor Island in the Philippines known for its rural communities and scenic seaside landscapes.
-
E.
Maria
Maria is a central character in Fritz Lang's classic science fiction film "Metropolis," known for her compassionate leadership and symbolic role as a mediator between social classes.
- 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 Cooper Janis, givenName, Maria]
Generated description
Maria is a feminine given name of Latin origin, widely used in many cultures and often associated with the Christian tradition.
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, widely used in many cultures and often associated with the Christian tradition.
-
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 the given name of Maria Christina of the Netherlands, a 19th-century Dutch princess and member of the House of Orange-Nassau.
-
C.
Maria
Maria is the given name of Anna Maria Spencer-Stanhope, a member of the English Spencer-Stanhope family.
-
D.
Maria
Maria is the given name of Maria Ludovika of Austria-Este, an Empress consort of Austria in the early 19th century.
-
E.
Maria
Maria is the given name of Angelo Maria Durini, an 18th-century Italian cardinal, diplomat, and patron of the arts.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9901e44bc8190966f87ae219d6bf4 |
completed | April 11, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4ad79c8190b1304942dc48c0ff |
completed | May 3, 2026, 8:41 a.m. |
| NEDg | Description generation | batch_69f70b37ebe081909ed2ae0f42ccad2d |
completed | May 3, 2026, 8:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70ca343f08190b6484f464ed40810 |
completed | May 3, 2026, 8:51 a.m. |
Created at: April 9, 2026, 9:25 p.m.