Triple
T29703701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Renshaw |
E751563
|
entity |
| Predicate | targetOfRevengeBy |
P69992
|
FINISHED |
| Object | victim’s mother (via toy soldiers) |
—
|
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: victim’s mother (via toy soldiers) | Statement: [John Renshaw, targetOfRevengeBy, victim’s mother (via toy soldiers)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfRevengeBy Context triple: [John Renshaw, targetOfRevengeBy, victim’s mother (via toy soldiers)]
-
A.
methodOfRevenge
Indicates a relationship where a specific action or strategy is used as the means by which revenge is carried out.
-
B.
aimedAtBy
chosen
Indicates that one entity serves as the target or goal toward which another entity directs an action, intention, or focus.
-
C.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
D.
causeOfVengeance
Indicates a relationship where one entity is the reason or trigger for another entity’s desire or act of vengeance.
-
E.
antagonistActionOf
Indicates that one entity performs an action in opposition or hostility toward another entity, acting as its antagonist.
- 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_69f0d6266f8481909e70bb41cda18587 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: April 28, 2026, 7:26 p.m.