Triple
T3103532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statute of Treasons 1351 |
E64775
|
entity |
| Predicate | pettyTreasonIncludes |
P45949
|
FINISHED |
| Object | servant killing his master |
—
|
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: servant killing his master | Statement: [Statute of Treasons 1351, pettyTreasonIncludes, servant killing his master]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pettyTreasonIncludes Context triple: [Statute of Treasons 1351, pettyTreasonIncludes, servant killing his master]
-
A.
hasTransgression
Indicates that one entity has committed, is responsible for, or is associated with a violation, offense, or wrongdoing in relation to another entity or rule.
-
B.
complicitIn
Indicates involvement in or knowing participation in a wrongful, illegal, or unethical act carried out by another party.
-
C.
guiltyOf
Indicates that an entity has been judged or determined to have committed a particular offense, crime, or wrongful act.
-
D.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
E.
accusedOf
Indicates that one entity has formally alleged or claimed that another entity committed a specific wrongdoing or offense.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada26f376c8190a049399e33314d52 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.