Triple
T33164716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worcester, Vermont |
E848848
|
entity |
| Predicate | distanceToMontpelier |
P88894
|
FINISHED |
| Object | approximately 10 miles |
—
|
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 10 miles | Statement: [Worcester, Vermont, distanceToMontpelier, approximately 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMontpelier Context triple: [Worcester, Vermont, distanceToMontpelier, approximately 10 miles]
-
A.
distanceToMontpelierApprox
chosen
Indicates an approximate measure of how far one entity is from Montpelier, typically expressed as a distance value.
-
B.
distanceToMontgomery
Indicates the spatial distance between a given entity and the location identified as Montgomery.
-
C.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
-
D.
distanceToAnnapolisMiles
Indicates the physical distance, measured in miles, between a given location and Annapolis.
-
E.
distanceToMorgantownMi
Indicates the measured distance from a given entity or location to Morgantown, Michigan.
- 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_69f3495be8808190bbf427733df08aad |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:28 a.m.