Triple
T34101033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Model Human Processor |
E874568
|
entity |
| Predicate | representsHumanAs |
P72867
|
FINISHED |
| Object | information processing system |
—
|
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: information processing system | Statement: [Model Human Processor, representsHumanAs, information processing system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsHumanAs Context triple: [Model Human Processor, representsHumanAs, information processing system]
-
A.
isHuman
Indicates that the subject entity possesses the defining characteristics or status of being a human.
-
B.
isFullyHuman
Indicates that an entity possesses all defining characteristics of a human being, without any non-human or partial-human aspects.
-
C.
humanRepresentative
Indicates that one entity serves as a human agent or delegate acting on behalf of another entity.
-
D.
representsAs
chosen
Indicates that one entity serves as a depiction, symbol, or stand-in for another entity in some representational context.
-
E.
treatsHumansAs
Indicates how one entity regards or behaves toward humans, characterizing them in a particular way (e.g., as equals, tools, resources, or threats).
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
Created at: May 1, 2026, 1:53 a.m.