Triple
T1963540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedict |
E42638
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object |
Benedikta
Benedikta is a feminine given name derived from the Latin-rooted name Benedict, commonly used in various European languages.
|
E192548
|
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: Benedikta | Statement: [Benedict, hasFeminineForm, Benedikta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benedikta Context triple: [Benedict, hasFeminineForm, Benedikta]
-
A.
Aikaterine
Aikaterine is an ancient Greek female given name that is the linguistic ancestor of various forms such as Katherine and Kathleen.
-
B.
Beata Beatrix
Beata Beatrix is a celebrated painting by Dante Gabriel Rossetti that portrays a trance-like Beatrice and exemplifies the spiritual, symbolic style of the Pre-Raphaelite movement.
-
C.
Margareta
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
D.
Benedetta
Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
-
E.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
- 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: Benedikta Triple: [Benedict, hasFeminineForm, Benedikta]
Generated description
Benedikta is a feminine given name derived from the Latin-rooted name Benedict, commonly used in various European languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benedikta Target entity description: Benedikta is a feminine given name derived from the Latin-rooted name Benedict, commonly used in various European languages.
-
A.
Aikaterine
Aikaterine is an ancient Greek female given name that is the linguistic ancestor of various forms such as Katherine and Kathleen.
-
B.
Beata Beatrix
Beata Beatrix is a celebrated painting by Dante Gabriel Rossetti that portrays a trance-like Beatrice and exemplifies the spiritual, symbolic style of the Pre-Raphaelite movement.
-
C.
Margareta
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
D.
Benedetta
chosen
Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
-
E.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3ac31a08190abaecac8badc52c7 |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae031ef4e48190af93dfd6f33184d3 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae0386785c8190ae74e5f04a4809fc |
completed | March 8, 2026, 11:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae042728f48190850848116a371794 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.