Triple
T37336905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juhu Beach |
E926915
|
entity |
| Predicate | timeOfPeakCrowd |
P196345
|
FINISHED |
| Object | evenings |
—
|
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: evenings | Statement: [Juhu Beach, timeOfPeakCrowd, evenings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfPeakCrowd Context triple: [Juhu Beach, timeOfPeakCrowd, evenings]
-
A.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
B.
circulationPeak
Indicates the highest level or maximum point reached in the circulation of something (such as money, media, or resources) within a given period or system.
-
C.
hasNumberOfSeatsAtPeak
Indicates the maximum number of seats available or occupied at the peak usage or capacity of something.
-
D.
circulationPeakPeriod
Indicates the time period during which circulation (such as distribution or flow) reaches its highest level.
-
E.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
| PDg | Predicate description generation | batch_69fe21afdc4c8190913ac4b55a9a5f52 |
completed | May 8, 2026, 5:47 p.m. |
Created at: May 3, 2026, 4:16 p.m.