Triple
T10180881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laetitia |
E236777
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Laetitiae
Laetitiae is a Latin variant form of the name Laetitia, traditionally associated with joy and happiness.
|
E846341
|
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: Laetitiae | Statement: [Laetitia, hasVariant, Laetitiae]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laetitiae Context triple: [Laetitia, hasVariant, Laetitiae]
-
A.
Erminia
Erminia is a compassionate and conflicted princess in Torquato Tasso’s epic poem "Gerusalemme liberata," known for her unrequited love for the Christian knight Tancredi and her dramatic flight from the battlefield.
-
B.
Cornelia
Cornelia is a feminine given name of Latin origin, historically associated with several notable women in European history.
-
C.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
D.
Aelia
Aelia was a Roman noblewoman best known as an early wife of the powerful Roman general and dictator Lucius Cornelius Sulla.
-
E.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
- 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: Laetitiae Triple: [Laetitia, hasVariant, Laetitiae]
Generated description
Laetitiae is a Latin variant form of the name Laetitia, traditionally associated with joy and happiness.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laetitiae Target entity description: Laetitiae is a Latin variant form of the name Laetitia, traditionally associated with joy and happiness.
-
A.
Erminia
Erminia is a compassionate and conflicted princess in Torquato Tasso’s epic poem "Gerusalemme liberata," known for her unrequited love for the Christian knight Tancredi and her dramatic flight from the battlefield.
-
B.
Cornelia
Cornelia is a feminine given name of Latin origin, historically associated with several notable women in European history.
-
C.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
D.
Aelia
Aelia was a Roman noblewoman best known as an early wife of the powerful Roman general and dictator Lucius Cornelius Sulla.
-
E.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded315f14819085727bd9b4363d10 |
completed | April 2, 2026, 4:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d301373a008190b8d39a8db4167e4f |
completed | April 6, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69d3028994fc81908507449a10e7e093 |
completed | April 6, 2026, 12:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d3031ed1e88190b9906338285a6e46 |
completed | April 6, 2026, 12:49 a.m. |
Created at: March 30, 2026, 9:11 p.m.