Triple
T19220956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Gabriel da Cachoeira |
E480610
|
entity |
| Predicate | timeZoneAbbreviation |
P714
|
FINISHED |
| Object | AMT |
—
|
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: AMT | Statement: [São Gabriel da Cachoeira, timeZoneAbbreviation, AMT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AMT Context triple: [São Gabriel da Cachoeira, timeZoneAbbreviation, AMT]
-
A.
AMT
AMT is the standard time zone used in Armenia, corresponding to UTC+4 hours.
-
B.
AMT
AMT is the National Rail station code for Aldermaston railway station in Berkshire, England.
-
C.
Amazon Time (AMT)
chosen
Amazon Time (AMT) is a Brazilian time zone used in parts of the Amazon region, including the city of Manaus.
-
D.
AMTK
AMTK is the reporting mark used by Amtrak, the United States’ national passenger railroad service, to identify its locomotives and rolling stock.
-
E.
AMAT
AMAT is the stock ticker symbol for Applied Materials, a leading American company that supplies equipment, services, and software for the semiconductor and display industries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa3e8d488190a93fb743dabd0ffb |
completed | April 20, 2026, 10:04 a.m. |
Created at: April 10, 2026, 1:24 p.m.