Triple
T37653705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Democracy in Plural Societies |
E937239
|
entity |
| Predicate | proposesModelFor |
P41880
|
FINISHED |
| Object | governing deeply divided societies |
—
|
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: governing deeply divided societies | Statement: [Democracy in Plural Societies, proposesModelFor, governing deeply divided societies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposesModelFor Context triple: [Democracy in Plural Societies, proposesModelFor, governing deeply divided societies]
-
A.
possibleModel
chosen
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
B.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
-
C.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
D.
namespaceModel
Indicates a relationship where a model is defined within, or associated with, a particular namespace or logical grouping.
-
E.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
- 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_69f76ed4fe908190b8061c5c135e0971 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.