Triple

T17280219
Position Surface form Disambiguated ID Type / Status
Subject Anna Maria E419505 entity
Predicate hasSpellingVariant P457 FINISHED
Object Annamaria
Annamaria is a feminine given name, typically considered a combined form of "Anna" and "Maria" used in various European cultures.
 E1260700 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: Annamaria | Statement: [Anna Maria, hasSpellingVariant, Annamaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Annamaria
Context triple: [Anna Maria, hasSpellingVariant, Annamaria]
  • A. Antonina
    Antonina is one of the three central women whose intertwined personal and professional lives are followed over several decades in the Soviet drama film "Moscow Does Not Believe in Tears."
  • B. Antonina
    Antonina is a historical novel by Wilkie Collins set in ancient Rome during the Gothic siege of the city.
  • C. Antonina
    Antonina was a prominent Byzantine noblewoman and influential wife of the famed general Belisarius, noted for her political acumen and close association with Empress Theodora in the 6th century.
  • D. Giovannina
    Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
  • E. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • 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: Annamaria
Triple: [Anna Maria, hasSpellingVariant, Annamaria]
Generated description
Annamaria is a feminine given name, typically considered a combined form of "Anna" and "Maria" used in various European cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Annamaria
Target entity description: Annamaria is a feminine given name, typically considered a combined form of "Anna" and "Maria" used in various European cultures.
  • A. Antonina
    Antonina is one of the three central women whose intertwined personal and professional lives are followed over several decades in the Soviet drama film "Moscow Does Not Believe in Tears."
  • B. Antonina
    Antonina is a historical novel by Wilkie Collins set in ancient Rome during the Gothic siege of the city.
  • C. Antonina
    Antonina was a prominent Byzantine noblewoman and influential wife of the famed general Belisarius, noted for her political acumen and close association with Empress Theodora in the 6th century.
  • D. Giovannina
    Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
  • E. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e43329904c8190a4cbc856b9b94ff8 completed April 19, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0179513ffc81908bac515823e88a1a completed May 11, 2026, 6:38 a.m.
NEDg Description generation batch_6a017c351e908190bcd7bb751dc7f949 completed May 11, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_6a017cad99688190aeaa388bf2d7d603 completed May 11, 2026, 6:52 a.m.
Created at: April 10, 2026, 5:40 a.m.