Triple
T4882886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mall of Scandinavia |
E109370
|
entity |
| Predicate | hasIMAXScreen |
P59602
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mall of Scandinavia, hasIMAXScreen, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIMAXScreen Context triple: [Mall of Scandinavia, hasIMAXScreen, yes]
-
A.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
B.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
C.
hasAuditorium
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
D.
theaterSupport
Indicates that one entity provides assistance, resources, or services to support another entity in the context of theater or theatrical activities.
-
E.
filmSettingTheater
Indicates that a film’s setting or key scenes take place in a theater (such as a cinema or playhouse).
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddfff0c81908fb148a6f6508334 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2be5e881909f6ec9c3bcde49f3 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6d5976a081909090c0c263f6e9b7 |
completed | March 20, 2026, 3:52 p.m. |
Created at: March 20, 2026, 1:27 p.m.