Triple
T4198827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Butcher of Amritsar |
E86016
|
entity |
| Predicate | moralJudgment |
P42941
|
FINISHED |
| Object | condemnation of Reginald Dyer’s actions |
—
|
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: condemnation of Reginald Dyer’s actions | Statement: [The Butcher of Amritsar, moralJudgment, condemnation of Reginald Dyer’s actions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralJudgment Context triple: [The Butcher of Amritsar, moralJudgment, condemnation of Reginald Dyer’s actions]
-
A.
moralJudgmentOn
chosen
Indicates that one entity evaluates or assesses the morality of another entity, action, or situation.
-
B.
moralImplication
Indicates that one situation, action, or state of affairs entails or suggests a particular moral judgment, obligation, or ethical consequence.
-
C.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
-
D.
moralTone
Indicates the evaluative moral quality or ethical character expressed in or associated with an action, statement, or situation.
-
E.
moralConcept
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af036243b4819097efe6b796823cd9 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:48 p.m.