Triple
T16636462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ros |
E404216
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Rosalie |
unclear NED1
|
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: Rosalie | Statement: [Ros, relatedName, Rosalie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosalie Context triple: [Ros, relatedName, Rosalie]
-
A.
Rosalie
"Rosalie" is a popular song by composer Cole Porter, featured in the Ella Fitzgerald album "Ella Fitzgerald Sings the Cole Porter Song Book."
-
B.
Rosalie
"Rosalie" is a rock song popularized by Irish band Thin Lizzy, known for its energetic style and storytelling lyrics.
-
C.
Rosalie
Rosalie is a musical comedy best known for its Broadway production featuring music by George Gershwin and Sigmund Romberg.
-
D.
Rosalie
Rosalie is the given first name of American actress and model Andie MacDowell.
-
E.
Rosaliac
Rosaliac is a La Roche-Posay skincare line formulated to soothe, strengthen, and visibly reduce redness in sensitive, redness-prone skin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378ea4b848190bf7c95dad8a855f0 |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dc28df48190b01c1328df24df60 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.