Triple
T5953220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Mound, Washington |
E132447
|
entity |
| Predicate | locatedInTimeZoneUTCOffset |
P109
|
FINISHED |
| Object | UTC−08:00 |
—
|
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: UTC−08:00 | Statement: [Grand Mound, Washington, locatedInTimeZoneUTCOffset, UTC−08:00]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTimeZoneUTCOffset Context triple: [Grand Mound, Washington, locatedInTimeZoneUTCOffset, UTC−08:00]
-
A.
locatedInTimeZone
chosen
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
-
B.
partlyLocatedInTimeZone
Indicates that an entity’s extent overlaps multiple time zones, with at least part of it falling within the specified time zone.
-
C.
locatedInTimeZoneDatabaseCountry
Indicates that the entity is situated in, or associated with, a country as defined in the time zone database.
-
D.
relatedTimeZone
Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
-
E.
timeZoneDependence
Indicates how a process, value, or behavior changes or is determined based on the time zone in which it is considered.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.