Triple
T12650244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lago General Carrera |
E302136
|
entity |
| Predicate | areaInArgentina |
P157
|
FINISHED |
| Object | ~880 km² |
—
|
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: ~880 km² | Statement: [Lago General Carrera, areaInArgentina, ~880 km²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaInArgentina Context triple: [Lago General Carrera, areaInArgentina, ~880 km²]
-
A.
ianaArea
Indicates that one entity is associated with, or falls within, a specific IANA-defined geographic or administrative area represented by the other entity.
-
B.
unitArgentina
Indicates a relationship where an entity is associated with, belongs to, or is characterized as a unit related to Argentina.
-
C.
landArea
chosen
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
argentineSectorPartOf
Indicates that one entity is a sector or subdivision that forms a component part of a larger Argentine administrative or geographic unit.
-
E.
metroArea
Indicates that one location is part of, or belongs to, a specified metropolitan area.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:18 p.m.