Triple
T4633222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jirón Junín |
E101465
|
entity |
| Predicate | hasPavement |
P14456
|
FINISHED |
| Object | urban roadway pavement |
—
|
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: urban roadway pavement | Statement: [Jirón Junín, hasPavement, urban roadway pavement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPavement Context triple: [Jirón Junín, hasPavement, urban roadway pavement]
-
A.
isPavedMostOfWay
Indicates that a route or path is surfaced with pavement for the majority of its length, though not necessarily entirely.
-
B.
pavedWith
chosen
Indicates that a surface or area is covered or constructed using a specified material as its paving.
-
C.
hasSidewalk
Indicates that a location, path, or roadway is accompanied by a designated sidewalk area for pedestrian use.
-
D.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
E.
hasPedestrianArea
Indicates that a location or zone includes a designated area intended for pedestrian use only or primarily.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a5d0de881909baacc5b991f5b53 |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.