Triple
T16531967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USGS National Map |
E401587
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | National Land Cover Database |
E1212843
|
NE 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: National Land Cover Database | Statement: [USGS National Map, hasComponent, National Land Cover Database]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: National Land Cover Database Context triple: [USGS National Map, hasComponent, National Land Cover Database]
-
A.
National Land Cover Database
chosen
The National Land Cover Database is a comprehensive U.S. land cover and land use mapping product that provides consistent, nationwide geospatial data for environmental monitoring, land management, and research.
-
B.
National Hydrography Dataset
The National Hydrography Dataset is a comprehensive digital geospatial database that maps the surface water features of the United States, including streams, rivers, lakes, and related hydrologic information for analysis and cartography.
-
C.
Global Land Survey datasets
Global Land Survey datasets are long-term, globally consistent satellite imagery collections designed to support land cover mapping, environmental monitoring, and change detection over multiple decades.
-
D.
Forest Global Earth Observatory
Forest Global Earth Observatory is an international research network that monitors long-term dynamics of forest ecosystems across the globe to understand biodiversity, climate impacts, and forest health.
-
E.
CDIAC
CDIAC is the acronym for the California Debt and Investment Advisory Commission, a state body that provides guidance, education, and data on public debt issuance and investment practices in California.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed8075c81908ff47396879abd0c |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00609129808190b893346e06deb944 |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:15 a.m.