Triple
T38544854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orin Scrivello |
E924937
|
entity |
| Predicate | relationshipTypeWith Audrey |
P10690
|
FINISHED |
| Object | abusive boyfriend |
—
|
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: abusive boyfriend | Statement: [Orin Scrivello, relationshipTypeWith Audrey, abusive boyfriend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Audrey Context triple: [Orin Scrivello, relationshipTypeWith Audrey, abusive boyfriend]
-
A.
relationshipTypeWith Audrey Bingham
Indicates the specific nature or category of relational connection that an entity has with Audrey Bingham.
-
B.
hasRelationshipTypeWith Alexandra Bergson
Indicates that there exists a specific type or category of relationship between an entity and Alexandra Bergson.
-
C.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
D.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
relationshipToAlice
Indicates the specific type of relationship or connection that an entity has with Alice.
- 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_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.