Triple
T9550747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte |
E230414
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Charlotta
Charlotta is a feminine given name, commonly used in various European countries as a form of Charlotte.
|
E805397
|
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: Charlotta | Statement: [Charlotte, hasVariant, Charlotta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlotta Context triple: [Charlotte, hasVariant, Charlotta]
-
A.
Izabel
Izabel is a feminine given name, commonly used in various cultures as a variant of Isabel or Isabella.
-
B.
Katherine
Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
-
C.
Katherine
Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
-
D.
Mary Desha
Mary Desha was an American educator and civic leader best known as one of the four co-founders of the patriotic lineage organization Daughters of the American Revolution.
-
E.
Christiana
Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
- 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: Charlotta Triple: [Charlotte, hasVariant, Charlotta]
Generated description
Charlotta is a feminine given name, commonly used in various European countries as a form of Charlotte.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charlotta Target entity description: Charlotta is a feminine given name, commonly used in various European countries as a form of Charlotte.
-
A.
Izabel
Izabel is a feminine given name, commonly used in various cultures as a variant of Isabel or Isabella.
-
B.
Katherine
Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
-
C.
Katherine
Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
-
D.
Mary Desha
Mary Desha was an American educator and civic leader best known as one of the four co-founders of the patriotic lineage organization Daughters of the American Revolution.
-
E.
Christiana
Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
- 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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd991df7308190a56d95f195627513 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c85b9208190acf98fa985b0f01f |
completed | April 4, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_69d14d0c39c88190a705470104dc7b80 |
completed | April 4, 2026, 5:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14d79065081908a4e619c71e0d359 |
completed | April 4, 2026, 5:42 p.m. |
Created at: March 30, 2026, 8:02 p.m.