Triple
T7748213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manly Beacon |
E175685
|
entity |
| Predicate | popularTimeToVisit |
P78489
|
FINISHED |
| Object | sunrise |
—
|
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: sunrise | Statement: [Manly Beacon, popularTimeToVisit, sunrise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularTimeToVisit Context triple: [Manly Beacon, popularTimeToVisit, sunrise]
-
A.
seasonalTourism
Indicates that tourism activity in a place varies significantly by season, with distinct peak and off-peak periods.
-
B.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
C.
countryDuringPeak
Indicates the country in which an entity was located or primarily associated during its peak period of activity, influence, or performance.
-
D.
popularSeason
Indicates that a particular season is widely liked, favored, or frequently chosen by many people.
-
E.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
- F. None of above. chosen
Provenance (4 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c70524c3948190a163dc5f4ecdffa7 |
completed | March 27, 2026, 10:31 p.m. |
Created at: March 27, 2026, 4:08 p.m.