Triple
T14130728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harlen Maguire |
E350156
|
entity |
| Predicate | notableFeatureInStory |
P112925
|
FINISHED |
| Object | photographs crime scenes |
—
|
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: photographs crime scenes | Statement: [Harlen Maguire, notableFeatureInStory, photographs crime scenes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFeatureInStory Context triple: [Harlen Maguire, notableFeatureInStory, photographs crime scenes]
-
A.
notableFeatureOn
Indicates that one entity is a prominent or distinguishing feature located on or part of another entity.
-
B.
notableStory
Indicates that an entity is the subject or source of a story, account, or narrative that is considered notable or significant.
-
C.
notableStoryArc
Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
-
D.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
-
E.
notableStorySubject
Indicates that the subject is a prominent or central topic, character, or element within a particular story or narrative.
- F. None of above. chosen
Provenance (4 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610aa434819096671c5aabb9134a |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:47 p.m.