Triple
T16681043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zofia Teofila Daniłowicz |
E405337
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Teofila
Teofila is a feminine given name of Polish origin historically borne by several notable women in the Polish–Lithuanian Commonwealth.
|
E1227620
|
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: Teofila | Statement: [Zofia Teofila Daniłowicz, givenName, Teofila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teofila Context triple: [Zofia Teofila Daniłowicz, givenName, Teofila]
-
A.
Thereza
Thereza is a given name, most commonly a variant spelling of Theresa used as a feminine first name in various cultures.
-
B.
Adelfia
Adelfia is a town and comune in the Apulia region of southern Italy, known for its agricultural traditions and religious festivals.
-
C.
Filitosa
Filitosa is a renowned prehistoric archaeological site in southern Corsica, famous for its Bronze Age megalithic statues and stone structures.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
- 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: Teofila Triple: [Zofia Teofila Daniłowicz, givenName, Teofila]
Generated description
Teofila is a feminine given name of Polish origin historically borne by several notable women in the Polish–Lithuanian Commonwealth.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teofila Target entity description: Teofila is a feminine given name of Polish origin historically borne by several notable women in the Polish–Lithuanian Commonwealth.
-
A.
Thereza
Thereza is a given name, most commonly a variant spelling of Theresa used as a feminine first name in various cultures.
-
B.
Adelfia
Adelfia is a town and comune in the Apulia region of southern Italy, known for its agricultural traditions and religious festivals.
-
C.
Filitosa
Filitosa is a renowned prehistoric archaeological site in southern Corsica, famous for its Bronze Age megalithic statues and stone structures.
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6f5cf481909e7628bbaa884e5a |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a404f448190a9dc7831382ffcdc |
completed | May 10, 2026, 1:38 p.m. |
| NEDg | Description generation | batch_6a008aed0bfc8190886b6a2e08a885b9 |
completed | May 10, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008bc0e57c8190838ec383f2a1b52c |
completed | May 10, 2026, 1:44 p.m. |
Created at: April 10, 2026, 5:19 a.m.