Triple
T2340243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Land Ordinance of 1785 |
E45008
|
entity |
| Predicate | definedTownshipSize |
P7759
|
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: [Land Ordinance of 1785, definedTownshipSize, 6 miles by 6 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definedTownshipSize Context triple: [Land Ordinance of 1785, definedTownshipSize, 6 miles by 6 miles]
-
A.
hasNumberOfAcres
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
B.
fieldSize
chosen
Indicates the magnitude or dimensions of a field associated with an entity or context.
-
C.
sectionsPerTownship
Indicates the number of land sections that are contained within a single township.
-
D.
requiredShareOfLand
Indicates the proportion or amount of land that must be allocated or possessed to satisfy a specified requirement or rule.
-
E.
hasTownship
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.