Triple
T7139385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Wild |
E166401
|
entity |
| Predicate | turnedInToAuthorities |
P75063
|
FINISHED |
| Object | thieves who did not cooperate with him |
—
|
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: thieves who did not cooperate with him | Statement: [Jonathan Wild, turnedInToAuthorities, thieves who did not cooperate with him]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnedInToAuthorities Context triple: [Jonathan Wild, turnedInToAuthorities, thieves who did not cooperate with him]
-
A.
confessedTo
Indicates that one entity admitted guilt or revealed the truth about an action, wrongdoing, or secret to another entity.
-
B.
broughtToCourtBy
Indicates that a person or entity is taken to court or legally prosecuted by another party.
-
C.
consideredCriminalBy
Indicates that one party regards or classifies another party as a criminal according to its own laws, rules, or judgments.
-
D.
turnedPro
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
-
E.
prosecuted
Indicates that legal authorities have formally brought criminal charges against an entity and pursued a case against them in a court of law.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7759a048190815689298befa8d7 |
completed | March 27, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:45 p.m.