Triple
T5122482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosemarie Trockel |
E115501
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rosemarie |
E489518
|
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: Rosemarie | Statement: [Rosemarie Trockel, givenName, Rosemarie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosemarie Context triple: [Rosemarie Trockel, givenName, Rosemarie]
-
A.
Rosemarie
chosen
Rosemarie is a feminine given name, typically considered a variant of Rosemary, used in various European and English-speaking cultures.
-
B.
Rose-Marie
Rose-Marie is a popular 1924 operetta, with music by Rudolf Friml, known for its romantic plot set in the Canadian Rockies and songs like "Indian Love Call."
-
C.
Maryanne
Maryanne is a feminine given name, often used in English-speaking countries as a variant of Mary Ann or Marianne.
-
D.
Madelyn
Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
-
E.
Madelaine
Madelaine is a character in the Danish crime thriller film "The Salvation."
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78045e448190961db0ca7692370e |
completed | March 20, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4b401a481909abf6660401c47dc |
completed | March 21, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:42 p.m.