Triple
T17534311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Böhmer |
E427016
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Caroline |
—
|
NE NERFINISHED |
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: Caroline | Statement: [Caroline Böhmer, givenName, Caroline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caroline Context triple: [Caroline Böhmer, givenName, Caroline]
-
A.
Caroline
Caroline was a British princess of the early 18th century, the daughter of King George II and Queen Caroline of Ansbach.
-
B.
Caroline
chosen
Caroline is a feminine given name of French and Latin origin, commonly used in English-speaking and European countries.
-
C.
Caroline
Caroline is a rural town in Tompkins County, New York, known for its small communities, scenic landscapes, and proximity to the city of Ithaca.
-
D.
Caroline
"Caroline" is a breakout hip-hop single by American rapper Aminé, known for its catchy hook and playful storytelling.
-
E.
Caroline
Caroline is a Danish princess, known formally as Princess Wilhelmina Caroline of Denmark, who lived in the 18th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536ac7f48190994f7b39a6a811d7 |
completed | April 19, 2026, 4 a.m. |
Created at: April 10, 2026, 5:49 a.m.