Triple
T17734202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brighton, Michigan |
E442669
|
entity |
| Predicate | distanceToLansing |
P128798
|
FINISHED |
| Object | approximately 50 miles east of Lansing |
—
|
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: approximately 50 miles east of Lansing | Statement: [Brighton, Michigan, distanceToLansing, approximately 50 miles east of Lansing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLansing Context triple: [Brighton, Michigan, distanceToLansing, approximately 50 miles east of Lansing]
-
A.
distanceToDetroit
Indicates the measured or calculated spatial distance between a given entity and the location of Detroit.
-
B.
distanceToMadison
Indicates the spatial distance between a given entity and the location identified as Madison.
-
C.
distanceToAnnArborApproxMiles
Indicates an approximate distance, measured in miles, between a given entity’s location and Ann Arbor.
-
D.
distanceToMilwaukee
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Milwaukee.
-
E.
distanceToColumbus
Indicates the spatial distance between a given entity and the location of Columbus.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e98a00819089490be2aa36873d |
completed | April 19, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d37ab6988190bd326ea6f8dd4aaa |
completed | April 18, 2026, 6:54 p.m. |
Created at: April 10, 2026, 10:08 a.m.