Triple
T3302940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Rapids and Indiana Railroad |
E69376
|
entity |
| Predicate | connectedArea |
P2564
|
FINISHED |
| Object | southern Michigan to northern Michigan |
—
|
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: southern Michigan to northern Michigan | Statement: [Grand Rapids and Indiana Railroad, connectedArea, southern Michigan to northern Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectedArea Context triple: [Grand Rapids and Indiana Railroad, connectedArea, southern Michigan to northern Michigan]
-
A.
connectsArea
chosen
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
B.
representedArea
Indicates that one entity serves as a representation or depiction of a particular area or region.
-
C.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
D.
engagementArea
Indicates the spatial region or scope within which an entity’s actions, influence, or interactions are intended to occur.
-
E.
areaComponent
Indicates that one area is a constituent or sub-area that forms part of a larger area.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0c662308190aad8b2a93e1c8a5c |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada42625308190be257f16a623a410 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.