Triple
T18086179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Malcolm |
E432838
|
entity |
| Predicate | hasRelationshipStatus |
P105779
|
FINISHED |
| Object | divorced |
—
|
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: divorced | Statement: [John Malcolm, hasRelationshipStatus, divorced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipStatus Context triple: [John Malcolm, hasRelationshipStatus, divorced]
-
A.
romanticRelationshipStatus
Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
-
B.
relationshipStatusInStory
Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
-
C.
companionshipStatus
Indicates the current state or condition of a relationship of companionship between two or more entities.
-
D.
hasCivilStatus
chosen
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
E.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd150ab88190864be2a722d214b8 |
completed | April 19, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:27 a.m.