Triple
T38376315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xo Viet Nghe Tinh Street |
E893630
|
entity |
| Predicate | typicalTrafficMode |
P27465
|
FINISHED |
| Object | motorbikes |
—
|
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: motorbikes | Statement: [Xo Viet Nghe Tinh Street, typicalTrafficMode, motorbikes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrafficMode Context triple: [Xo Viet Nghe Tinh Street, typicalTrafficMode, motorbikes]
-
A.
hasTrafficMode
Indicates the mode or type of traffic associated with or applicable to an entity (e.g., pedestrian, vehicular, public transit).
-
B.
majorTrafficType
chosen
Indicates the primary kind of traffic or flow that predominantly characterizes a given route, segment, or transportation context.
-
C.
coversTrafficType
Indicates that one entity includes, handles, or applies to a specified type or category of traffic.
-
D.
typicalLanes
Indicates the usual or standard number or configuration of lanes associated with a road or similar transportation segment.
-
E.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
- 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_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.