Triple
T5174280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llanquihue Lake |
E116758
|
entity |
| Predicate | rankByAreaInChile |
P62164
|
FINISHED |
| Object | second-largest lake in Chile |
—
|
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: second-largest lake in Chile | Statement: [Llanquihue Lake, rankByAreaInChile, second-largest lake in Chile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInChile Context triple: [Llanquihue Lake, rankByAreaInChile, second-largest lake in Chile]
-
A.
hasPopulationRankInChile
Indicates the relative position of an entity in the ordered ranking of populations within Chile.
-
B.
isPartOfChileanTerritory
Indicates that one entity is geographically or politically included within the official territory of Chile.
-
C.
distanceFromSantiago
Indicates the spatial distance between a given entity and the location of Santiago.
-
D.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
-
E.
rankInChinaByArea
Indicates the position of an entity in an ordered list of entities in China when sorted by their area size.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7971284481909e6d07b2368a4f76 |
completed | March 20, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69bd77b529948190b86671ebe43f4734 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79251b548190918a1eb930e24c22 |
completed | March 20, 2026, 4:43 p.m. |
Created at: March 20, 2026, 1:45 p.m.