Triple
T1577487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Graciosa |
E33685
|
entity |
| Predicate | hasRoadCharacteristic |
P1777
|
FINISHED |
| Object | mostly unpaved roads |
—
|
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: mostly unpaved roads | Statement: [La Graciosa, hasRoadCharacteristic, mostly unpaved roads]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadCharacteristic Context triple: [La Graciosa, hasRoadCharacteristic, mostly unpaved roads]
-
A.
hasRoadConfiguration
Indicates that there exists a specific arrangement or layout of roads associated with or characterizing an entity.
-
B.
roadFeature
chosen
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
C.
hasCarriagewayType
Indicates the specific structural or functional type of carriageway associated with a road segment (e.g., single, dual, or other carriageway configurations).
-
D.
isPublicRoad
Indicates that a given road is officially designated and accessible for use by the general public.
-
E.
roadwayCarries
Indicates that a roadway serves as a route that supports or conveys a particular transportation facility, traffic flow, or designated use.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907ba63c88190b60c14dec8d1e40f |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.