Triple
T28333189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gismonda |
E717587
|
entity |
| Predicate | hasOriginalProducer |
P182834
|
FINISHED |
| Object | Sarah Bernhardt |
—
|
NE NERFINISHED |
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: Sarah Bernhardt | Statement: [Gismonda, hasOriginalProducer, Sarah Bernhardt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalProducer Context triple: [Gismonda, hasOriginalProducer, Sarah Bernhardt]
-
A.
hasOriginalVersion
Indicates that one entity is the original or initial version from which another entity is derived or adapted.
-
B.
originallyProducedAs
Indicates that one entity was first created, released, or manufactured in the form of another specified entity or format.
-
C.
hasOriginalWorkSetting
Indicates that an entity is associated with the setting or context in which the original work or source material takes place.
-
D.
hasOriginalPart
Indicates that an entity includes a component or segment that is part of its initial, original composition.
-
E.
hasOriginalComposition
Indicates that one entity is the initial or primary compositional source or makeup of another entity.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: April 28, 2026, 12:33 a.m.