Triple
T33300183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddy Slade |
E852557
|
entity |
| Predicate | hasPastRelationshipType |
P143101
|
FINISHED |
| Object | high school romance with Mavis Gary |
—
|
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: high school romance with Mavis Gary | Statement: [Buddy Slade, hasPastRelationshipType, high school romance with Mavis Gary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPastRelationshipType Context triple: [Buddy Slade, hasPastRelationshipType, high school romance with Mavis Gary]
-
A.
formerRelationshipStatus
chosen
Indicates that a relationship between entities existed in the past but no longer holds in the present.
-
B.
wasInRelationshipDuring
Indicates that two entities were in a romantic or otherwise defined interpersonal relationship with each other during a specified time period.
-
C.
hadPartnerType
Indicates that an entity was associated with another entity in a specific type or category of partnership.
-
D.
hadPartner
Indicates that an entity was in a romantic or life-partner relationship with another entity at some point in time.
-
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_69f34966ed4c81908dc9dda82d8c7fe3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: May 1, 2026, 1:33 a.m.