Triple
T3530948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Sussex |
E74658
|
entity |
| Predicate | locatedOnTimeZone |
P109
|
FINISHED |
| Object | Europe/London |
—
|
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: Europe/London | Statement: [University of Sussex, locatedOnTimeZone, Europe/London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedOnTimeZone Context triple: [University of Sussex, locatedOnTimeZone, Europe/London]
-
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.
relatedTimeZone
Indicates that two entities are associated with or operate within the same or corresponding time zone(s).
-
D.
timeZonePractice
Indicates that an entity conducts activities or operations according to a particular time zone or set of time zone rules.
-
E.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc988ee081909c6b9d5eed0d2d6d |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.