Triple
T3258652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolf Friml |
E68358
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
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."
|
E356235
|
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: Rose-Marie | Statement: [Rudolf Friml, notableWork, Rose-Marie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rose-Marie Context triple: [Rudolf Friml, notableWork, Rose-Marie]
-
A.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
B.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
C.
Therese
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
-
D.
Marie
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
-
E.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
- 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: Rose-Marie Triple: [Rudolf Friml, notableWork, Rose-Marie]
Generated description
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."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rose-Marie Target entity description: 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."
-
A.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
B.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
C.
Therese
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
-
D.
Marie
Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
-
E.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adafa4f40c81909adfd0f7f568e3ce |
completed | March 8, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b35456814c8190a8e4d53935af539a |
completed | March 13, 2026, 12:03 a.m. |
| NEDg | Description generation | batch_69b35546dfa0819081800009fbe8afe3 |
completed | March 13, 2026, 12:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b355cecc4c81908ecb5f83e89b4a00 |
completed | March 13, 2026, 12:09 a.m. |
Created at: March 8, 2026, 3:09 p.m.