Triple
T30470670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | METRO Orange Line |
E775282
|
entity |
| Predicate | priorityFeatures |
P7153
|
FINISHED |
| Object | bus-only lanes |
—
|
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: bus-only lanes | Statement: [METRO Orange Line, priorityFeatures, bus-only lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: priorityFeatures Context triple: [METRO Orange Line, priorityFeatures, bus-only lanes]
-
A.
primarySettingFeature
Indicates that a particular feature is the main or defining characteristic of a setting.
-
B.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
priorityBenefit
Indicates that one benefit takes precedence over or is considered more important than another in a given context.
-
D.
keyFeature
chosen
Indicates that something is a primary, distinguishing, or most important feature of an entity.
-
E.
priorityApplication
Indicates that one application is given precedence or higher processing priority over others.
- 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_69f2249622a48190b1fae2e3e4ee958a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68714edd88190a49ba653a0360961 |
completed | May 2, 2026, 11:21 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:11 p.m.