Triple
T21122609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trg Oslobođenja |
E520468
|
entity |
| Predicate | hasUsageTime |
P70126
|
FINISHED |
| Object | used year-round |
—
|
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: used year-round | Statement: [Trg Oslobođenja, hasUsageTime, used year-round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUsageTime Context triple: [Trg Oslobođenja, hasUsageTime, used year-round]
-
A.
hasScreenTimeIn
Indicates that an entity appears on screen for a certain duration within a specified audiovisual work or segment.
-
B.
hasTypicalUseTime
chosen
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
-
C.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
D.
hasServiceTime
Indicates that an entity is associated with a specific duration or schedule during which a service is provided.
-
E.
hasAllocatedTime
Indicates that a specific amount or period of time has been reserved or assigned for a particular entity, task, or activity.
- 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7223587008190a2b35ea06cf6508b |
completed | April 21, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:55 p.m.