Triple
T25955174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yalan Dünya |
E654073
|
entity |
| Predicate | hasRecurringLocation |
P26564
|
FINISHED |
| Object | Istanbul neighborhood |
—
|
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: Istanbul neighborhood | Statement: [Yalan Dünya, hasRecurringLocation, Istanbul neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringLocation Context triple: [Yalan Dünya, hasRecurringLocation, Istanbul neighborhood]
-
A.
recurringLocation
chosen
Indicates that an event, action, or state happens repeatedly at the specified location over time.
-
B.
hasRecurringSetArea
Indicates that an entity is associated with an area or region that repeats or recurs according to a defined pattern or schedule.
-
C.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
D.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
E.
repeatLocation
Indicates that an entity occurs or appears multiple times at the same location or position.
- 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_69e7ab40ac788190a771bc499eb1ae5f |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 22, 2026, 8:44 a.m.