Triple
T13989942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dayton, New Jersey |
E336541
|
entity |
| Predicate | hasCommercialCorridorAlong |
P112071
|
FINISHED |
| Object | U.S. Route 130 |
—
|
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: U.S. Route 130 | Statement: [Dayton, New Jersey, hasCommercialCorridorAlong, U.S. Route 130]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialCorridorAlong Context triple: [Dayton, New Jersey, hasCommercialCorridorAlong, U.S. Route 130]
-
A.
locatedInTransportCorridor
Indicates that an entity is situated within a designated transport corridor used for the movement of people or goods.
-
B.
isIndustrialCorridor
Indicates that an area or route is designated and used primarily for industrial activities, facilities, or transportation.
-
C.
hasMajorCityOnRoute
Indicates that a major city lies along, or is directly served by, a specified route or path between locations.
-
D.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
E.
transportationCorridorType
Indicates the specific kind or classification of a transportation corridor (such as road, rail, or waterway) that characterizes how the route is used for movement or transit.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb22e388190904fc87765176c91 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:18 p.m.