Triple
T22825594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town Hall, Amritsar |
E565648
|
entity |
| Predicate | culturalProgramming |
P50054
|
FINISHED |
| Object | hosts exhibitions |
—
|
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: hosts exhibitions | Statement: [Town Hall, Amritsar, culturalProgramming, hosts exhibitions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalProgramming Context triple: [Town Hall, Amritsar, culturalProgramming, hosts exhibitions]
-
A.
hasCulturalProgram
chosen
Indicates that an entity offers or participates in an organized set of cultural activities, events, or initiatives.
-
B.
culturalType
Indicates the classification of something according to its cultural category, style, or tradition.
-
C.
culturalCategory
Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
-
D.
culturalScene
Indicates a relationship where an entity is associated with, participates in, or characterizes a particular cultural environment, milieu, or set of cultural activities.
-
E.
culturalSphere
Indicates that one entity belongs to, is influenced by, or participates in the cultural domain, tradition, or milieu defined by another entity.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dd47ea48190b32b2a7d37d95654 |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:34 p.m.