Triple
T12650243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lago General Carrera |
E302136
|
entity |
| Predicate | areaInChile |
P105993
|
FINISHED |
| Object | ~970 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: ~970 km² | Statement: [Lago General Carrera, areaInChile, ~970 km²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaInChile Context triple: [Lago General Carrera, areaInChile, ~970 km²]
-
A.
rankByAreaInChile
Indicates the relative ordering of entities based on their area size within the geographic boundaries of Chile.
-
B.
isPartOfChileanTerritory
Indicates that one entity is geographically or politically included within the official territory of Chile.
-
C.
hasPopulationRankInChile
Indicates the relative position of an entity in the ordered ranking of populations within Chile.
-
D.
ianaArea
Indicates that one entity is associated with, or falls within, a specific IANA-defined geographic or administrative area represented by the other entity.
-
E.
distanceFromSantiago
Indicates the spatial distance between a given entity and the location of Santiago.
- 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_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. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:18 p.m.