Triple
T12661635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East 10th Street and Second Avenue |
E302437
|
entity |
| Predicate | roadTypeStreet2 |
P1019
|
FINISHED |
| Object | north–south avenue (Second Avenue) |
—
|
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: north–south avenue (Second Avenue) | Statement: [East 10th Street and Second Avenue, roadTypeStreet2, north–south avenue (Second Avenue)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadTypeStreet2 Context triple: [East 10th Street and Second Avenue, roadTypeStreet2, north–south avenue (Second Avenue)]
-
A.
roadType
chosen
Indicates the classification or category of a road based on its functional or physical characteristics.
-
B.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
-
C.
streetSet
Indicates that a particular street belongs to, or is included within, a specified set or collection of streets.
-
D.
hasStreetDirection
Indicates that a street or road segment is associated with a specific directional orientation (e.g., northbound, east-west).
-
E.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617c5b888190b37d4ede139bb49e |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:19 p.m.