Triple
T16039290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Matheson |
E389050
|
entity |
| Predicate | hasRelationshipStatusInSeries |
P104581
|
FINISHED |
| Object | in a relationship with Patrick Murray |
—
|
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: in a relationship with Patrick Murray | Statement: [Kevin Matheson, hasRelationshipStatusInSeries, in a relationship with Patrick Murray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipStatusInSeries Context triple: [Kevin Matheson, hasRelationshipStatusInSeries, in a relationship with Patrick Murray]
-
A.
relationshipStatusInStory
chosen
Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
-
B.
hasStatusInSeries
Indicates that an entity holds a particular status or role within a specific series or sequence.
-
C.
relationshipStatusDuringFilm
Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
-
D.
hasSiblingSeriesAppearance
Indicates that two entities appear as siblings within the same series or narrative work.
-
E.
seriesStatus
Indicates the current state or phase of a series within its lifecycle (e.g., ongoing, completed, canceled, or planned).
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.