Triple
T28522960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Laymon |
E721835
|
entity |
| Predicate | workCharacteristics |
P34961
|
FINISHED |
| Object | high levels of violence |
—
|
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: high levels of violence | Statement: [Richard Laymon, workCharacteristics, high levels of violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workCharacteristics Context triple: [Richard Laymon, workCharacteristics, high levels of violence]
-
A.
workCharacter
Indicates that a person is a fictional or narrative character appearing in a particular creative work.
-
B.
employmentCharacteristic
Indicates a specific attribute, condition, or quality associated with a person’s employment or job situation.
-
C.
workAttribute
chosen
Indicates that a particular characteristic, quality, or property is associated with a specific work or piece of work.
-
D.
workDescribedAs
Indicates that one entity’s work, project, or output is characterized, labeled, or referred to by a particular description, title, or phrase.
-
E.
workDescribes
Indicates that one work (such as a document, artwork, or dataset) provides a description or explanatory account of another work.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64fa3116c8190a479c01ac94bbcb3 |
completed | May 2, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:22 a.m.