Triple
T8587358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Market Square, Helsinki |
E203338
|
entity |
| Predicate | openingPattern |
P27375
|
FINISHED |
| Object | mainly active in daytime |
—
|
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: mainly active in daytime | Statement: [Market Square, Helsinki, openingPattern, mainly active in daytime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingPattern Context triple: [Market Square, Helsinki, openingPattern, mainly active in daytime]
-
A.
typicalOpeningPattern
chosen
Indicates that there is a commonly occurring or characteristic initial configuration, sequence, or arrangement associated with the given context.
-
B.
openingMotif
Indicates that one element serves as the initial recurring theme or pattern that introduces and sets the tone for another element, such as a work or sequence.
-
C.
openingPractice
Indicates the practice or rehearsal of opening moves, procedures, or initial actions in a given context.
-
D.
openingSituation
Indicates the initial state, context, or set of conditions that exist at the beginning of an event, interaction, or narrative.
-
E.
openingAnswer
Indicates that an entity provides an initial or first response in a dialogue, interaction, or sequence of answers.
- 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_69ca8329bb7c8190a63c643730839103 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46c5e8888190b721e791c449b0df |
completed | March 31, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cc454504448190aaad2af8b17357cd |
completed | March 31, 2026, 10:05 p.m. |
Created at: March 30, 2026, 6:23 p.m.