Triple
T9237852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law & Order: Criminal Intent |
E221981
|
entity |
| Predicate | oftenDepictsEventsFrom |
P58519
|
FINISHED |
| Object | criminals' point of view |
—
|
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: criminals' point of view | Statement: [Law & Order: Criminal Intent, oftenDepictsEventsFrom, criminals' point of view]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenDepictsEventsFrom Context triple: [Law & Order: Criminal Intent, oftenDepictsEventsFrom, criminals' point of view]
-
A.
portraysEvent
Indicates that one entity depicts, represents, or illustrates a particular event.
-
B.
basedOnEventsDescribedIn
Indicates that something is derived from, inspired by, or constructed using the events described in another source.
-
C.
workOftenDepicts
chosen
Indicates that one entity’s work frequently portrays, represents, or includes the other entity as a subject or theme.
-
D.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
E.
perspectiveOnEvents
Indicates a relationship where an entity holds or expresses a particular interpretive viewpoint or framing regarding one or more events.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf09f9e908190801fe114c5e63984 |
completed | April 1, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:30 p.m.