Triple
T31733530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Democrat Coalition |
E809923
|
entity |
| Predicate | positionOnInnovationEconomy |
P89497
|
FINISHED |
| Object | supports knowledge-based economy |
—
|
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: supports knowledge-based economy | Statement: [New Democrat Coalition, positionOnInnovationEconomy, supports knowledge-based economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnInnovationEconomy Context triple: [New Democrat Coalition, positionOnInnovationEconomy, supports knowledge-based economy]
-
A.
innovationArea
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
B.
innovationLevel
Indicates the degree or extent to which something is new, original, or creatively advanced compared to existing norms or solutions.
-
C.
portraysInnovation
Indicates that one entity depicts, represents, or conveys the idea of innovation in relation to another entity.
-
D.
hasInnovationType
Indicates that an entity is associated with, or classified by, a specific type or category of innovation.
-
E.
positionOnEconomicSystem
chosen
Indicates the stance or viewpoint an entity holds regarding a particular economic system or model.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
Created at: April 30, 2026, 11:22 p.m.