Triple
T2434126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Rays with Neck Ribbon |
E52914
|
entity |
| Predicate | recognizesField |
P1597
|
FINISHED |
| Object | public administration |
—
|
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: public administration | Statement: [Gold Rays with Neck Ribbon, recognizesField, public administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognizesField Context triple: [Gold Rays with Neck Ribbon, recognizesField, public administration]
-
A.
supportsField
Indicates that one entity provides the necessary structure, stability, or backing for a particular field, area, or domain associated with another entity.
-
B.
coversField
Indicates that one entity extends over, protects, or occupies the surface or area of a field associated with another entity.
-
C.
fieldOfRecognition
chosen
Indicates the domain, discipline, or area in which an entity is formally acknowledged, honored, or recognized.
-
D.
definesField
Indicates that one entity specifies or declares a particular field or attribute that belongs to or characterizes another entity.
-
E.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:43 p.m.