Triple
T13053218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azores Time |
E327497
|
entity |
| Predicate | typicalOffsetFromMainlandPortugal |
P108475
|
FINISHED |
| Object | −1 hour |
—
|
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: −1 hour | Statement: [Azores Time, typicalOffsetFromMainlandPortugal, −1 hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffsetFromMainlandPortugal Context triple: [Azores Time, typicalOffsetFromMainlandPortugal, −1 hour]
-
A.
distanceFromLisbon
Indicates the measured spatial distance between a given entity’s location and the city of Lisbon.
-
B.
timeZoneOnSpanishSide
Indicates that the referenced time zone applies specifically to the Spanish side of a border or region.
-
C.
limitedPortugalTo
Indicates that something is restricted in scope, effect, or applicability specifically to Portugal.
-
D.
distanceFromPorto
Indicates the measured distance between a given place or entity and the city of Porto.
-
E.
isThreeQuartersOfAnHourAheadOf
Indicates that one entity’s time occurs exactly 45 minutes later than the other entity’s time.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
| PDg | Predicate description generation | batch_69d98a9577d081908ddef9ea77e408e2 |
completed | April 10, 2026, 11:41 p.m. |
Created at: April 9, 2026, 8:58 p.m.