Triple
T35158392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa Compton |
E1015190
|
entity |
| Predicate | themeOfWorkAppearedIn |
P129784
|
FINISHED |
| Object | generational conflict |
—
|
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: generational conflict | Statement: [Melissa Compton, themeOfWorkAppearedIn, generational conflict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeOfWorkAppearedIn Context triple: [Melissa Compton, themeOfWorkAppearedIn, generational conflict]
-
A.
themeOfWorkHeAppearsIn
Indicates that the subject is the thematic focus or central topic of the work in which he appears.
-
B.
settingOfWorkAppearsIn
Indicates that a particular place, time, or environment serves as the setting within which a given creative work’s events or narrative occur.
-
C.
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.
-
D.
appearsInWorkByAuthorFrom
Indicates that an entity appears in a work that was created by an author originating from a specified place or country.
-
E.
appearsInWorkByTitle
Indicates that an entity appears in, is featured in, or is contained within a work identified by its title.
- 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_69f76ddb3a708190b521ba2970b17178 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.