Triple
T16952984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shivers (title track) |
E411228
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object |
Susana
Susana is a Dutch trance vocalist known for her emotive performances and collaborations with prominent electronic music producers.
|
E1244808
|
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: Susana | Statement: [Shivers (title track), featuredArtist, Susana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susana Context triple: [Shivers (title track), featuredArtist, Susana]
-
A.
Susana
Susana is a feminine given name used in various cultures, often considered a variant of Susanna and associated with meanings related to "lily."
-
B.
Suzana
Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
-
C.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
D.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
E.
Rosa Elena
Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
- 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: Susana Triple: [Shivers (title track), featuredArtist, Susana]
Generated description
Susana is a Dutch trance vocalist known for her emotive performances and collaborations with prominent electronic music producers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Susana Target entity description: Susana is a Dutch trance vocalist known for her emotive performances and collaborations with prominent electronic music producers.
-
A.
Susana
Susana is a feminine given name used in various cultures, often considered a variant of Susanna and associated with meanings related to "lily."
-
B.
Suzana
Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
-
C.
Rosana
Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
-
D.
Rosana
Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
-
E.
Rosa Elena
Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01a4ae8819085a6ce01fbc71b0f |
completed | April 18, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc06e6b481908d8032f5772762c9 |
completed | May 10, 2026, 7:27 p.m. |
| NEDg | Description generation | batch_6a0114d33cac819083d8e542ea5bc274 |
completed | May 10, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0115c967b0819088e2335fd45d755b |
completed | May 10, 2026, 11:33 p.m. |
Created at: April 10, 2026, 5:31 a.m.