Triple
T29599161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Third Law of Robotics |
E754391
|
entity |
| Predicate | hasNormType |
P2826
|
FINISHED |
| Object | conditional obligation |
—
|
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: conditional obligation | Statement: [Third Law of Robotics, hasNormType, conditional obligation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNormType Context triple: [Third Law of Robotics, hasNormType, conditional obligation]
-
A.
hasNorm
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
B.
hasNormativeCategory
Indicates that something is associated with a particular normative category, such as a standard, rule, or evaluative classification that prescribes how it ought to be regarded or treated.
-
C.
normType
chosen
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
-
D.
haveNormalization
Indicates that one entity serves as a normalization or standardized form of another entity.
-
E.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69ffcf46fd688190907fd1ceb499a8d1 |
completed | May 10, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69ffccde2a8c81908e055e74077dbd19 |
completed | May 10, 2026, 12:10 a.m. |
Created at: April 28, 2026, 6:20 p.m.