Triple
T22642826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Recife |
E558875
|
entity |
| Predicate | pythonZoneInfoKey |
P149043
|
FINISHED |
| Object | America/Recife |
—
|
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: America/Recife | Statement: [America/Recife, pythonZoneInfoKey, America/Recife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pythonZoneInfoKey Context triple: [America/Recife, pythonZoneInfoKey, America/Recife]
-
A.
pythonPytzID
Indicates that an entity is associated with a specific time zone identifier as defined by the Python `pytz` library.
-
B.
javaTimeZoneID
Indicates that an entity is associated with a specific Java time zone identifier (e.g., "America/New_York") used for date and time operations.
-
C.
timeZoneName
Indicates the specific time zone designation (such as its standard name or label) associated with an entity.
-
D.
timeZoneDatabase
Indicates that there is an association between something (such as a system, service, or region) and a specific time zone database it uses or is defined by.
-
E.
MicrosoftTimeZoneIdentifier
Indicates the specific Microsoft-defined time zone identifier associated with an entity or event.
- F. None of above. chosen
Provenance (4 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1703577948190ae044df4f8500bfe |
completed | April 29, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:04 p.m.