Triple
T30084273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Hate-Good |
E764558
|
entity |
| Predicate | treatsAsCrime |
P61328
|
FINISHED |
| Object | true Christian faith |
—
|
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: true Christian faith | Statement: [Lord Hate-Good, treatsAsCrime, true Christian faith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsAsCrime Context triple: [Lord Hate-Good, treatsAsCrime, true Christian faith]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
consideredCriminalBy
chosen
Indicates that one party regards or classifies another party as a criminal according to its own laws, rules, or judgments.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific crime.
-
E.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 29, 2026, 7:03 p.m.