Triple
T3269043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carine |
E68597
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Caren |
E168871
|
NE FINISHED |
How this triple was built (2 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: Caren | Statement: [Carine, hasVariant, Caren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caren Context triple: [Carine, hasVariant, Caren]
-
A.
Caren
chosen
Caren is a feminine given name, typically considered a spelling variant of Karen.
-
B.
Carla
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
-
C.
Carine
Carine is a feminine given name, often considered a variant of names like Catherine or Karine, used in various European languages.
-
D.
Karin
Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
-
E.
Cynthia
Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafd0eddc8190834a64f6b8e8e9f9 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28efded588190bd6c361e5298b496 |
completed | March 12, 2026, 10:01 a.m. |
Created at: March 8, 2026, 3:09 p.m.