Triple
T27845855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina–Uruguay border |
E703817
|
entity |
| Predicate | timeZoneSide2 |
P163413
|
FINISHED |
| Object | Uruguay Standard Time |
—
|
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: Uruguay Standard Time | Statement: [Argentina–Uruguay border, timeZoneSide2, Uruguay Standard Time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZoneSide2 Context triple: [Argentina–Uruguay border, timeZoneSide2, Uruguay Standard Time]
-
A.
timeZoneSide1
chosen
Indicates that the first entity is associated with or located in a particular time zone.
-
B.
timeZoneOnUSSide
Indicates that the referenced time zone is the one used on the United States side of a border, region, or cross-national context.
-
C.
timeZoneOnChineseSide
Indicates that the referenced time zone is the one used on the Chinese side of a border, boundary, or cross-border context.
-
D.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
-
E.
timeZoneState
Indicates that one entity is a state or region associated with the time zone of another entity.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 6:07 p.m.