Triple
T15537581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mária |
E370388
|
entity |
| Predicate | hasGermanEquivalent |
P22792
|
FINISHED |
| Object |
Maria
Maria is a common female given name used in many languages, often associated with Christian traditions and derived from the Hebrew name Miriam.
|
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: [Mária, hasGermanEquivalent, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Mária, hasGermanEquivalent, Maria]
-
A.
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.
-
B.
Maria
Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
-
C.
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.
-
D.
Maria
Maria I of Portugal was the first queen regnant of Portugal, known for her devout Catholicism, initial period of enlightened reforms, and later mental illness that led to her son acting as regent.
-
E.
Maria
Maria is a witty and sharp-tongued lady-in-waiting to the Princess of France in William Shakespeare’s comedy "Love's Labour's Lost."
- 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: [Mária, hasGermanEquivalent, Maria]
Generated description
Maria is a common female given name used in many languages, often associated with Christian traditions and derived from the Hebrew name Miriam.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Target entity description: Maria is a common female given name used in many languages, often associated with Christian traditions and derived from the Hebrew name Miriam.
-
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 a woman known primarily as the daughter of Theophilus.
-
E.
Maria
Maria is the given name of Archduchess Anna Maria Sophia of Austria, a member of the Habsburg royal family.
- 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_69ff56bdbca08190b5eb541c5eb4bb09 |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff577e0ed08190a8f10f9e57c0e967 |
completed | May 9, 2026, 3:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff584b7b28819096fd2fad58ca32d6 |
completed | May 9, 2026, 3:52 p.m. |
Created at: April 10, 2026, 4:06 a.m.