Triple
T20937514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Carrera Lake (Chilean sector) |
E515624
|
entity |
| Predicate | hasLandformOnShore |
P85723
|
FINISHED |
| Object | cliffs |
—
|
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: cliffs | Statement: [General Carrera Lake (Chilean sector), hasLandformOnShore, cliffs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandformOnShore Context triple: [General Carrera Lake (Chilean sector), hasLandformOnShore, cliffs]
-
A.
hasCityOnShore
Indicates that a city is located on or directly adjacent to the shore of a body of water.
-
B.
hasShoreOn
Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
-
C.
hasStructureOnShore
Indicates that a structure is located on or directly adjacent to the shore of a body of water.
-
D.
primaryIslandOnShore
Indicates that one island is the main or most significant island located along a particular shore or coastline.
-
E.
shoreHas
chosen
Indicates that a shore possesses, contains, or is characterized by a particular feature, object, or attribute.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f9534cd48190a86665fb1df6b077 |
completed | April 21, 2026, 4:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:49 p.m.