Triple
T36206341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Lyman |
E1047405
|
entity |
| Predicate | themeOfAssociatedWork |
P129784
|
FINISHED |
| Object | murder investigation |
—
|
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: murder investigation | Statement: [Peter Lyman, themeOfAssociatedWork, murder investigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeOfAssociatedWork Context triple: [Peter Lyman, themeOfAssociatedWork, murder investigation]
-
A.
associatedWithAuthorTheme
Indicates a relationship where an author is linked to, or characterized by, a particular theme in their work or thought.
-
B.
subjectOfWorkBy
chosen
Indicates that one entity is the main topic or focus of a work (such as a book, article, or artwork) created by another entity.
-
C.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
D.
associatedWithWorkTheme
Indicates a relationship where something is connected or related to a particular work theme or subject matter.
-
E.
genreOfWorkAbout
Indicates that a work is about a particular genre, expressing that the work’s subject matter or focus concerns that genre.
- 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_69f76e4214748190a76c986d2a1838c2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:09 p.m.