Triple
T30444129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soai Kinh Lam fabric market |
E774528
|
entity |
| Predicate | typicalPeakTime |
P57188
|
FINISHED |
| Object | morning |
—
|
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: morning | Statement: [Soai Kinh Lam fabric market, typicalPeakTime, morning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPeakTime Context triple: [Soai Kinh Lam fabric market, typicalPeakTime, morning]
-
A.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
B.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
C.
peakHours
chosen
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
D.
operationalPeriodPeak
Indicates the time span during which something operates at its maximum or peak level of activity or performance.
-
E.
timeOfPeakCrowd
Indicates the specific time period during which the crowd size reaches its maximum level.
- 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:08 p.m.