Triple
T38376318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xo Viet Nghe Tinh Street |
E893630
|
entity |
| Predicate | timeOfPeakTraffic |
P57188
|
FINISHED |
| Object | morning rush hour |
—
|
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 rush hour | Statement: [Xo Viet Nghe Tinh Street, timeOfPeakTraffic, morning rush hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfPeakTraffic Context triple: [Xo Viet Nghe Tinh Street, timeOfPeakTraffic, morning rush hour]
-
A.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
B.
timeOfPeakCrowd
Indicates the specific time period during which the crowd size reaches its maximum level.
-
C.
circulationPeakPeriod
Indicates the time period during which circulation (such as distribution or flow) reaches its highest level.
-
D.
activityPeakPeriod
Indicates the time period during which an activity reaches its highest level or intensity.
-
E.
peakHours
chosen
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
- 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_69f76e4b1f748190a380696a16eae4a2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe6fea4a288190bf8615c5d6bf41b4 |
completed | May 8, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69fe6f774de08190975a2393b9a1fd22 |
completed | May 8, 2026, 11:19 p.m. |
Created at: May 3, 2026, 4:31 p.m.