Triple
T3559127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theresa |
E75291
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Tereza
Tereza is a feminine given name, commonly used in various European languages as a form of Theresa.
|
E271573
|
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: Tereza | Statement: [Theresa, hasVariant, Tereza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tereza Context triple: [Theresa, hasVariant, Tereza]
-
A.
Milena
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
-
B.
Magda
Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
-
C.
Verena
Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
-
D.
Terézia
Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
-
E.
Marta
Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
- 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: Tereza Triple: [Theresa, hasVariant, Tereza]
Generated description
Tereza is a feminine given name, commonly used in various European languages as a form of Theresa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tereza Target entity description: Tereza is a feminine given name, commonly used in various European languages as a form of Theresa.
-
A.
Milena
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
-
B.
Magda
Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
-
C.
Verena
Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
-
D.
Terézia
chosen
Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
-
E.
Marta
Marta is a legendary Brazilian footballer widely regarded as one of the greatest women’s players of all time.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0881d50819092332491b9527c9d |
completed | March 8, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bb9983f48190bda2749d93c74a8d |
completed | March 13, 2026, 7:24 a.m. |
| NEDg | Description generation | batch_69b3bcae84a48190b085f253773cd14f |
completed | March 13, 2026, 7:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3f90df47c81908855021f68ca7ec8 |
completed | March 13, 2026, 11:46 a.m. |
Created at: March 8, 2026, 3:20 p.m.