Triple
T33502538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddy Gale |
E858031
|
entity |
| Predicate | targetOfVengeance |
P61789
|
FINISHED |
| Object | John Booth |
—
|
NE NERFINISHED |
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: John Booth | Statement: [Freddy Gale, targetOfVengeance, John Booth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfVengeance Context triple: [Freddy Gale, targetOfVengeance, John Booth]
-
A.
methodOfRevenge
Indicates a relationship where a specific action or strategy is used as the means by which revenge is carried out.
-
B.
causeOfVengeance
chosen
Indicates a relationship where one entity is the reason or trigger for another entity’s desire or act of vengeance.
-
C.
targetOfAntagonists
Indicates that the referenced entity is the object or focus of hostile actions, opposition, or conflict initiated by antagonistic parties.
-
D.
antagonistActionOf
Indicates that one entity performs an action in opposition or hostility toward another entity, acting as its antagonist.
-
E.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe779248c081909f0ed1a2a0df23db |
completed | May 8, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69fe76eaf6d48190998bc7168749cc42 |
completed | May 8, 2026, 11:51 p.m. |
Created at: May 1, 2026, 1:38 a.m.