Triple
T6781925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Enriquillo |
E155702
|
entity |
| Predicate | isOneOfLowest |
P13885
|
FINISHED |
| Object | points in the Caribbean |
—
|
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: points in the Caribbean | Statement: [Lake Enriquillo, isOneOfLowest, points in the Caribbean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfLowest Context triple: [Lake Enriquillo, isOneOfLowest, points in the Caribbean]
-
A.
isSmallestOf
Indicates that an entity has the minimum size or value within a specified set or group of entities.
-
B.
hasLow
chosen
Indicates that an entity possesses a value, level, or amount of something that is below a defined or expected threshold.
-
C.
lowestRank
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
-
D.
isLargestOf
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
-
E.
isMinimumWhen
Indicates that a value or state is at its smallest or least level precisely under certain specified conditions or circumstances.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26c621c8190a6eddc0d395e13e4 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.