Triple
T1562813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodland Avenue |
E33364
|
entity |
| Predicate | hasStreetRunningTracks |
P29464
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Woodland Avenue, hasStreetRunningTracks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetRunningTracks Context triple: [Woodland Avenue, hasStreetRunningTracks, yes]
-
A.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
B.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
-
C.
hasWheelchairLanes
Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
-
D.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
-
E.
hasRailTrail
Indicates that one location or entity possesses, includes, or is connected by a rail trail (a recreational trail converted from or running along a former or existing railway corridor) to another location or entity.
- F. None of above. chosen
Provenance (4 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90fccd4b48190a44012888a00af7f |
completed | March 5, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69a907b872f0819096b3df6ad502c63e |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a90fcb8ca48190a9ee50559ba73b22 |
completed | March 5, 2026, 5:08 a.m. |
Created at: March 4, 2026, 7:27 p.m.