Triple
T24592545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O'Higgins Lake |
E608573
|
entity |
| Predicate | hasLanguageVariantNameInChile |
P105994
|
FINISHED |
| Object | Lago O'Higgins |
—
|
NE NERFINISHED |
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: Lago O'Higgins | Statement: [O'Higgins Lake, hasLanguageVariantNameInChile, Lago O'Higgins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageVariantNameInChile Context triple: [O'Higgins Lake, hasLanguageVariantNameInChile, Lago O'Higgins]
-
A.
hasNameInSpanish
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
hasNameInAymaraOrQuechua
Indicates that an entity is known by a specific name expressed in either the Aymara or Quechua language.
-
C.
nameInChile
chosen
Indicates that an entity is known or referred to by a particular name specifically within the context of Chile.
-
D.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish language.
-
E.
hasNameInMapudungun
Indicates that an entity is associated with a specific name expressed in the Mapudungun language.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9dc63208190b70f57b9821a7241 |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.