Triple
T25723554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ANILCA |
E645054
|
entity |
| Predicate | areaProtected |
P159020
|
FINISHED |
| Object | >100 million 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: >100 million acres | Statement: [ANILCA, areaProtected, >100 million acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaProtected Context triple: [ANILCA, areaProtected, >100 million acres]
-
A.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
-
B.
protectedAreaCountry
Indicates that a protected area is located within and legally falls under the jurisdiction of a specific country.
-
C.
percentageProtectedArea
Indicates the proportion of a given area that is designated and managed as protected land or water.
-
D.
protectedAreaEstablishedBy
Indicates that a protected area was formally created, designated, or brought into legal existence by a specific agent or authority.
-
E.
protectsArea
Indicates that one entity serves to guard, defend, or preserve a particular area or region from harm or intrusion.
- F. None of above. chosen
Provenance (4 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc692684819091fdaace59b40334 |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 10:07 p.m.