Triple
T18156454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portier (Monaco Grand Prix corner) |
E434642
|
entity |
| Predicate | cityStreetSection |
P5397
|
FINISHED |
| Object | public roads of Monte Carlo |
—
|
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: public roads of Monte Carlo | Statement: [Portier (Monaco Grand Prix corner), cityStreetSection, public roads of Monte Carlo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityStreetSection Context triple: [Portier (Monaco Grand Prix corner), cityStreetSection, public roads of Monte Carlo]
-
A.
streetSectionOf
chosen
Indicates that one street segment or portion belongs to, is contained within, or forms part of a larger street or roadway.
-
B.
streetSet
Indicates that a particular street belongs to, or is included within, a specified set or collection of streets.
-
C.
streetOrArea
Indicates that one entity is a street or area associated with, located at, or relevant to the other entity.
-
D.
urbanSegmentName
Indicates the specific name assigned to a segment within an urban area or city layout.
-
E.
cityStreetUsed
Indicates that a particular city street is utilized or traversed in the course of some activity, route, or event.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debe27a88190bd76c6f78fcf1bd1 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.