Triple
T33922041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reunification Express line |
E869639
|
entity |
| Predicate | typicalJourneyTimeHanoiToHoChiMinhHours |
P206737
|
FINISHED |
| Object | approximately 30–35 |
—
|
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: approximately 30–35 | Statement: [Reunification Express line, typicalJourneyTimeHanoiToHoChiMinhHours, approximately 30–35]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalJourneyTimeHanoiToHoChiMinhHours Context triple: [Reunification Express line, typicalJourneyTimeHanoiToHoChiMinhHours, approximately 30–35]
-
A.
distanceToHoChiMinhCity
Indicates the physical distance between a given location or entity and Ho Chi Minh City.
-
B.
travelTimeFromAoNang
Indicates the amount of time required to travel from Ao Nang to another specified location or entity.
-
C.
distanceFromHanoi
Indicates the spatial distance between a given location and Hanoi.
-
D.
distanceToHaLongCity
Indicates the measured or specified distance between a given location and Ha Long City.
-
E.
distanceToDaNang_km
Indicates the distance, measured in kilometers, between a given location and Da Nang.
- 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_69f349992c508190aa4afa24a086cc8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:49 a.m.