Triple
T10573677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Friday |
E249555
|
entity |
| Predicate | focusOfStories |
P80359
|
FINISHED |
| Object | criminal investigations in Los Angeles |
—
|
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: criminal investigations in Los Angeles | Statement: [Joe Friday, focusOfStories, criminal investigations in Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusOfStories Context triple: [Joe Friday, focusOfStories, criminal investigations in Los Angeles]
-
A.
seriesFocus
chosen
Indicates that one entity serves as the primary subject, theme, or focal point of a series created, presented, or organized by another entity.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
headOfStoryOn
Indicates that one entity serves as the main headline or leading title for a story that appears on another entity (such as a page or section).
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5274929cc81909a79d5e2049f7389 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:37 p.m.