Triple
T3703415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Dawes |
E80834
|
entity |
| Predicate | routeTaken |
P6174
|
FINISHED |
| Object | land route out of Boston Neck on April 18, 1775 |
—
|
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: land route out of Boston Neck on April 18, 1775 | Statement: [William Dawes, routeTaken, land route out of Boston Neck on April 18, 1775]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeTaken Context triple: [William Dawes, routeTaken, land route out of Boston Neck on April 18, 1775]
-
A.
routeVia
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
B.
routeBetween
Indicates that there exists a path or connection enabling travel or communication between two locations or points.
-
C.
approachRoute
chosen
Indicates the path or method taken by one entity as it moves toward or comes closer to another entity or target.
-
D.
routeOptimization
Indicates the process of determining the most efficient path or sequence of paths between locations according to specified criteria such as distance, time, or cost.
-
E.
wentTo
Indicates that one entity traveled or moved from its original location to another specified place.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54aaac88190b775dba2513b6d4a |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adb84eeca48190bb4de637e9f0e27a |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:33 p.m.