Triple
T6730562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Evil |
E153622
|
entity |
| Predicate | relationshipStatusWithDrEvil |
P73404
|
FINISHED |
| Object | strained |
—
|
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: strained | Statement: [Scott Evil, relationshipStatusWithDrEvil, strained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithDrEvil Context triple: [Scott Evil, relationshipStatusWithDrEvil, strained]
-
A.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
B.
relationshipToAnnDeever
Indicates the specific interpersonal or familial relationship that an entity has to Ann Deever.
-
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.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
relationshipToHeistCrew
Indicates the specific role, connection, or association an entity has with a particular heist crew.
- F. None of above. chosen
Provenance (4 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d35134148190b49fb5c25a0f8ed4 |
completed | March 27, 2026, 6:58 p.m. |
Created at: March 27, 2026, 2:09 p.m.