Triple
T252641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont D’Iberville |
E5182
|
entity |
| Predicate | hasGlacialFeatures |
P940
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mont D’Iberville, hasGlacialFeatures, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlacialFeatures Context triple: [Mont D’Iberville, hasGlacialFeatures, true]
-
A.
hasGlacier
Indicates that one entity possesses, contains, or is characterized by the presence of a glacier.
-
B.
notableGlacier
Indicates that the subject is a glacier recognized for its particular significance, prominence, or noteworthiness.
-
C.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
D.
hasLandform
chosen
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d39eb3881909f435043c8697f13 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b678d6c81909780e1995c1ca691 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.