Triple
T9505385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Jean-Paul-II |
E229254
|
entity |
| Predicate | hasPrimaryUseTime |
P70126
|
FINISHED |
| Object | 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: daytime | Statement: [Place Jean-Paul-II, hasPrimaryUseTime, daytime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryUseTime Context triple: [Place Jean-Paul-II, hasPrimaryUseTime, daytime]
-
A.
hasTypicalUseTime
chosen
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
-
B.
hasSecondaryUsage
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
-
C.
hasPrimaryFeature
Indicates that an entity possesses a main or most characteristic feature that defines or distinguishes it.
-
D.
hasTimeIndication
Indicates that something includes, specifies, or is associated with a particular time-related indication (such as a timestamp, time period, or temporal marker).
-
E.
hasTemporalUse
Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9850fe6c8190a5a96cfae12562c6 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:57 p.m.