Triple
T12862596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Cobb |
E307630
|
entity |
| Predicate | involvementType |
P82125
|
FINISHED |
| Object | body-sharing with Edwina Cutwater |
—
|
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: body-sharing with Edwina Cutwater | Statement: [Roger Cobb, involvementType, body-sharing with Edwina Cutwater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvementType Context triple: [Roger Cobb, involvementType, body-sharing with Edwina Cutwater]
-
A.
typeOfInvolvement
chosen
Indicates the specific role, capacity, or manner in which one entity is involved with or participates in another entity or activity.
-
B.
engagementType
Indicates the specific kind or category of engagement or interaction that occurs between the related entities.
-
C.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
D.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
E.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:37 p.m.