Triple
T32436048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai intercity coach network |
E828868
|
entity |
| Predicate | peakDemandPeriod |
P164182
|
FINISHED |
| Object | Chinese New Year travel season |
—
|
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: Chinese New Year travel season | Statement: [Shanghai intercity coach network, peakDemandPeriod, Chinese New Year travel season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakDemandPeriod Context triple: [Shanghai intercity coach network, peakDemandPeriod, Chinese New Year travel season]
-
A.
seasonalDemandPeak
chosen
Indicates that demand for a product, service, or resource reaches its highest level during a specific recurring season or time period.
-
B.
peakDemandUnit
Indicates the unit of measurement used to express the peak level of demand in a given context.
-
C.
peakHours
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
D.
peakDay
Indicates the specific day on which a quantity, activity, or effect reaches its maximum level within a given period.
-
E.
peakServicePeriod
Indicates the time interval during which a service experiences its highest or most intensive level of use or operation.
- 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_69f3491bf298819097b610f772d54a6d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2b48a8c8190a6ba0d2f084078cc |
completed | May 3, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:55 a.m.