Triple
T9416812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Smecker |
E227042
|
entity |
| Predicate | relationshipToVigilantes |
P89032
|
FINISHED |
| Object | initially pursues them as criminals |
—
|
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: initially pursues them as criminals | Statement: [Paul Smecker, relationshipToVigilantes, initially pursues them as criminals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToVigilantes Context triple: [Paul Smecker, relationshipToVigilantes, initially pursues them as criminals]
-
A.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
relationshipToHeistCrew
Indicates the specific role, connection, or association an entity has with a particular heist crew.
-
C.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
D.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
E.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cb4be08190a47f901a9703f9db |
completed | April 1, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca9d07eb08190866eb15333386dfa |
completed | April 1, 2026, 5:14 a.m. |
Created at: March 30, 2026, 7:48 p.m.