Triple
T8815422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treadstone |
E209763
|
entity |
| Predicate | ethicalStatusInStory |
P22659
|
FINISHED |
| Object | morally ambiguous |
—
|
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: morally ambiguous | Statement: [Treadstone, ethicalStatusInStory, morally ambiguous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethicalStatusInStory Context triple: [Treadstone, ethicalStatusInStory, morally ambiguous]
-
A.
hasEthicalText
Indicates that an entity is associated with or contains text expressing ethical principles, guidelines, or considerations.
-
B.
hasMoralIssue
Indicates that there exists an ethical concern, dilemma, or conflict associated with the referenced entity or situation.
-
C.
hasEthicalConstraint
Indicates that an entity is subject to a specified ethical rule, limitation, or normative requirement that governs its behavior or decisions.
-
D.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
-
E.
moralStatus
chosen
Indicates the ethical standing or degree of moral consideration that one entity has 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ff2ff248190bafcafe8b3860e53 |
completed | March 31, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:45 p.m.