Triple
T35425780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Hailes Avenue |
E1023916
|
entity |
| Predicate | hasRoadsideFeature |
P107291
|
FINISHED |
| Object | commercial establishments |
—
|
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: commercial establishments | Statement: [Lady Hailes Avenue, hasRoadsideFeature, commercial establishments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadsideFeature Context triple: [Lady Hailes Avenue, hasRoadsideFeature, commercial establishments]
-
A.
hasRoadsideFacility
chosen
Indicates that a location or route segment is associated with a facility or service situated along its roadside.
-
B.
hasRoadCharacteristics
Indicates that one entity possesses specific road-related features or attributes, such as type, condition, or structural properties.
-
C.
roadsideFunction
Indicates that something serves a specific purpose or role related to the use, support, or operation of a roadside area.
-
D.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
E.
hasScenicPullouts
Indicates that a route or roadway includes designated scenic pullout areas where travelers can stop to view the surroundings.
- 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: May 3, 2026, 4:03 p.m.