Triple
T556305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Ridge |
E11947
|
entity |
| Predicate | transportationPattern |
P8986
|
FINISHED |
| Object | auto-oriented commuting |
—
|
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: auto-oriented commuting | Statement: [Lake Ridge, transportationPattern, auto-oriented commuting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportationPattern Context triple: [Lake Ridge, transportationPattern, auto-oriented commuting]
-
A.
transportationFunction
Indicates that one entity serves to move or carry another entity from one place to another.
-
B.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
C.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
D.
transportNetwork
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
E.
hasCommuterPattern
chosen
Indicates that there is a characteristic or recurring pattern in how an entity regularly travels between locations, typically for work or daily activities.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.