Triple
T22068206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Desert Land Act |
E545334
|
entity |
| Predicate | maximumAcreagePerEntry |
P19614
|
FINISHED |
| Object | 640 acres |
—
|
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: 640 acres | Statement: [Desert Land Act, maximumAcreagePerEntry, 640 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAcreagePerEntry Context triple: [Desert Land Act, maximumAcreagePerEntry, 640 acres]
-
A.
hasNumberOfAcres
chosen
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
-
B.
acquiredLandArea
Indicates the total area of land that has been obtained or taken possession of through an acquisition.
-
C.
hasCadastralArea
Indicates that an entity possesses or is associated with a specific cadastral (official land registry) area measurement.
-
D.
requiredShareOfLand
Indicates the proportion or amount of land that must be allocated or possessed to satisfy a specified requirement or rule.
-
E.
fieldSize
Indicates the magnitude or dimensions of a field associated with an entity or context.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12885fe04819092cdde142f91e147 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:27 p.m.