Triple
T2118861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Land Survey System |
E43869
|
entity |
| Predicate | standardTownshipSize |
P3664
|
FINISHED |
| Object | 6 miles by 6 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: 6 miles by 6 miles | Statement: [Public Land Survey System, standardTownshipSize, 6 miles by 6 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardTownshipSize Context triple: [Public Land Survey System, standardTownshipSize, 6 miles by 6 miles]
-
A.
typicalUnitSize
chosen
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
B.
majorAccessTown
Indicates that a location serves as a primary or significant access point to a town, such as a main route, gateway, or connection hub.
-
C.
hasTownship
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
-
D.
town
Indicates that a location is classified or functions as a town within a given geographic or administrative context.
-
E.
isSmallCity
Indicates that a city has a relatively small population size or limited geographic/urban extent compared to typical cities.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb3117c081908c5e748a869d1f9f |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.