Triple
T35488023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US-NE |
E1025650
|
entity |
| Predicate | assignedToSubdivisionOf |
P103735
|
FINISHED |
| Object | United States of America |
—
|
NE NERFINISHED |
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: United States of America | Statement: [US-NE, assignedToSubdivisionOf, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assignedToSubdivisionOf Context triple: [US-NE, assignedToSubdivisionOf, United States of America]
-
A.
associatedWithSubdivision
Indicates that one entity has a connection or linkage to a specific administrative or organizational subdivision.
-
B.
assignedUnder
Indicates that one entity has been given responsibility, duty, or authority to act within the scope, supervision, or framework defined by another entity.
-
C.
assignedToArea
Indicates that something has been allocated or designated to a specific area or region.
-
D.
allottedTo
Indicates that something has been assigned or allocated to a particular entity as its designated recipient or user.
-
E.
isLocatedInSubdivision
chosen
Indicates that one place or entity is situated within a more specific administrative or geographic subdivision of another area.
- 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_69f76dfbcdd881908c7b0b6bc502252b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.