Triple
T14613703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carina |
E343024
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Carine |
E68597
|
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: Carine | Statement: [Carina, relatedName, Carine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carine Context triple: [Carina, relatedName, Carine]
-
A.
Carine
chosen
Carine is a feminine given name, often considered a variant of names like Catherine or Karine, used in various European languages.
-
B.
Yvette
Yvette is the given first name of the acclaimed American singer Chaka Khan.
-
C.
Yvette
Yvette is a river in northern France that flows through the Île-de-France region and serves as a tributary of the Orge.
-
D.
Chantal
Chantal is a commune located in the Sud Department of Haiti.
-
E.
Chantal
Chantal is the central protagonist of the animated series "High Seas," around whom the show's main adventures and storylines revolve.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5cbcf08819084313bf28f0bb3e1 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:25 a.m.