Triple
T21945951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma Elson |
E541932
|
entity |
| Predicate | relationshipTypeWithReynoldsWoodcock |
P146644
|
FINISHED |
| Object | muse |
—
|
LITERAL 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: muse | Statement: [Alma Elson, relationshipTypeWithReynoldsWoodcock, muse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithReynoldsWoodcock Context triple: [Alma Elson, relationshipTypeWithReynoldsWoodcock, muse]
-
A.
relationshipTypeWithNickWells
Indicates the specific nature or category of relationship that an entity has with Nick Wells.
-
B.
relationshipTypeWithSidney Cochran
Indicates the specific nature or category of the relationship that an entity has with Sidney Cochran.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
-
E.
relationshipToJaneRizzoli
Indicates the specific familial, social, or professional relationship that one entity has to Jane Rizzoli.
- F. None of above. chosen
Provenance (4 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12427c2b48190949c41bd3be2d9f3 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb6991948190a428c3c3bfd1c3b8 |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:57 p.m.