Triple
T27849821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Clock at Alexanderplatz |
E703919
|
entity |
| Predicate | timeZonesDisplayed |
P137773
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [World Clock at Alexanderplatz, timeZonesDisplayed, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeZonesDisplayed Context triple: [World Clock at Alexanderplatz, timeZonesDisplayed, 24]
-
A.
timeZoneEndpoint
Indicates a connection or boundary point where a specific time zone applies or is defined.
-
B.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
C.
timeZoneState
Indicates that one entity is a state or region associated with the time zone of another entity.
-
D.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
-
E.
zoneCount
chosen
Indicates the number of distinct zones associated with or contained within a given entity or context.
- 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_69ef840e614c8190a88cf9638c14a265 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6895f0819088655277e45859a8 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 6:09 p.m.