Triple
T32058408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaco Phenomenon |
E818679
|
entity |
| Predicate | hasAssociatedRoadSystem |
P184398
|
FINISHED |
| Object | Great North Road |
—
|
NE NERFINISHED |
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: Great North Road | Statement: [Chaco Phenomenon, hasAssociatedRoadSystem, Great North Road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedRoadSystem Context triple: [Chaco Phenomenon, hasAssociatedRoadSystem, Great North Road]
-
A.
hasRoads
Indicates that there exist constructed road connections linking the related entities.
-
B.
hasRoadNetworkType
Indicates the type or classification of road network associated with or present in an entity.
-
C.
hasRoadComponent
Indicates that something includes, contains, or is composed of a specific road-related part or element.
-
D.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
E.
hasRoadNumberSystem
Indicates that a place or region uses a specific system for assigning numbers to its roads or highways.
- 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_69f348fdacec8190b9f74375ca3b2094 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7b0e3917481908a394680d76743c3 |
completed | May 3, 2026, 8:32 p.m. |
Created at: May 1, 2026, 12:21 a.m.