Triple
T35052098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Memphremagog |
E1011355
|
entity |
| Predicate | hasShorelineCountrySubdivision |
P185258
|
FINISHED |
| Object | Estrie, Quebec |
—
|
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: Estrie, Quebec | Statement: [Lake Memphremagog, hasShorelineCountrySubdivision, Estrie, Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShorelineCountrySubdivision Context triple: [Lake Memphremagog, hasShorelineCountrySubdivision, Estrie, Quebec]
-
A.
hasShorelineCountry
Indicates that a country possesses a coastline or land boundary directly adjacent to a particular body of water or coastal region.
-
B.
hasShorelineMunicipality
Indicates that a municipality is located along and directly borders the shoreline of a body of water.
-
C.
hasCoastline
Indicates that a geographic entity is bordered by and directly touches a sea or ocean along part of its boundary.
-
D.
hasCoastlineType
Indicates the specific nature or classification of the coastline associated with a geographic entity.
-
E.
hasCountryCoastline
Indicates that a country possesses a coastline along a sea or ocean.
- 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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 3, 2026, 4:01 p.m.