Triple
T31623792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio State Route 82 |
E806964
|
entity |
| Predicate | hasGeneralTerrain |
P189727
|
FINISHED |
| Object | urban and suburban |
—
|
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 and suburban | Statement: [Ohio State Route 82, hasGeneralTerrain, urban and suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeneralTerrain Context triple: [Ohio State Route 82, hasGeneralTerrain, urban and suburban]
-
A.
hasPrimaryTerrain
Indicates that an entity’s main or dominant type of terrain or land surface is a specified terrain category.
-
B.
involvesTerrain
Indicates that the relationship or action takes place in, across, or is directly affected by a specified type of terrain or landform.
-
C.
hasTerrainFor
Indicates that a location or area possesses terrain suitable or designated for a particular use, activity, or feature.
-
D.
hasAdvancedTerrain
Indicates that an entity possesses or is associated with terrain featuring complex, challenging, or enhanced physical characteristics beyond standard ground conditions.
-
E.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
- 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_69f348d7883c8190b6c13ab92b7ef076 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc9d0854c8190aa00093274afebb8 |
completed | May 6, 2026, 11:08 p.m. |
Created at: April 30, 2026, 10:42 p.m.