Triple
T14104722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Raymond Langston |
E339474
|
entity |
| Predicate | hasStoryArcType |
P39504
|
FINISHED |
| Object | serial killer 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: serial killer investigation | Statement: [Dr. Raymond Langston, hasStoryArcType, serial killer investigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoryArcType Context triple: [Dr. Raymond Langston, hasStoryArcType, serial killer investigation]
-
A.
hasProtagonistJourneyType
Indicates that a narrative work features a main character whose overarching journey follows a specific type or pattern (e.g., hero’s journey, coming-of-age, tragedy).
-
B.
hasStaffTypeInStory
Indicates that a story involves or is associated with a particular type or category of staff.
-
C.
notableStoryArc
chosen
Indicates that there exists a significant or prominent narrative storyline or plot development involving the subject.
-
D.
hasStoryPath
Indicates that there exists a defined narrative route or sequence of events connecting one entity to another within a story or interactive experience.
-
E.
hasSiblingInStory
Indicates that one character in a narrative has at least one sibling who also appears within the same story.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbd02888190bf07fd6d8769b61c |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.