Triple
T13097014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Millennium Park (Abuja) |
E310615
|
entity |
| Predicate | hasOpeningTime |
P43960
|
FINISHED |
| Object | daytime hours |
—
|
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 hours | Statement: [Millennium Park (Abuja), hasOpeningTime, daytime hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningTime Context triple: [Millennium Park (Abuja), hasOpeningTime, daytime hours]
-
A.
hasOpening
Indicates that one entity possesses or features an opening, gap, or entrance that allows access, passage, or exposure.
-
B.
openingTime
chosen
Indicates the time at which a place, service, or event begins operating or becomes accessible.
-
C.
has24HourOperations
Indicates that an entity operates continuously for 24 hours a day without closing.
-
D.
openingHoursCharacteristic
Indicates a relationship that specifies particular attributes or features of an entity’s opening hours, such as patterns, exceptions, or special conditions.
-
E.
hasOpeningSetting
Indicates that one entity (typically a narrative work) has its initial scene or setting located in the other 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9814e88a0819088418c792ce7aa57 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:04 p.m.