Triple
T28672439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holly Gibney |
E725761
|
entity |
| Predicate | adaptedInWork |
P81409
|
FINISHED |
| Object | Mr. Mercedes (TV series) |
—
|
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: Mr. Mercedes (TV series) | Statement: [Holly Gibney, adaptedInWork, Mr. Mercedes (TV series)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptedInWork Context triple: [Holly Gibney, adaptedInWork, Mr. Mercedes (TV series)]
-
A.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
-
B.
adaptedIntoWork
chosen
Indicates that an original work has been transformed or re-created into another work, typically in a different medium or format.
-
C.
adaptedWorkOfAuthor
Indicates that a work is an adaptation derived from, based on, or reinterpreting the original work of a specified author.
-
D.
adaptedAs
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
-
E.
adaptedWithin
Indicates that one entity has been modified, adjusted, or tailored to function appropriately within the context, scope, or boundaries defined by another entity.
- F. None of above.
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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 5:04 a.m.