Triple
T1615762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber Green |
E34713
|
entity |
| Predicate | supportsGoalOf |
P5689
|
FINISHED |
| Object | decarbonizing urban transport |
—
|
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: decarbonizing urban transport | Statement: [Uber Green, supportsGoalOf, decarbonizing urban transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsGoalOf Context triple: [Uber Green, supportsGoalOf, decarbonizing urban transport]
-
A.
legacyGoal
Indicates that an entity has a long-term, enduring objective or impact it aims to leave behind beyond its immediate actions or existence.
-
B.
supportsOutcome
chosen
Indicates that one entity contributes to enabling, sustaining, or improving the achievement of a particular outcome associated with another entity.
-
C.
goals
Indicates that an entity has objectives, targets, or desired outcomes it aims to achieve.
-
D.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
E.
laterGoal
Indicates that one goal occurs or is intended to be achieved after another goal in time.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.