Triple
T447156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treaty of Paris (1783) |
E7046
|
entity |
| Predicate | southernBoundaryReference |
P13333
|
FINISHED |
| Object | 31st parallel north |
—
|
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: 31st parallel north | Statement: [Treaty of Paris (1783), southernBoundaryReference, 31st parallel north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: southernBoundaryReference Context triple: [Treaty of Paris (1783), southernBoundaryReference, 31st parallel north]
-
A.
hasSouthernTerminus
Indicates that one entity serves as the southern endpoint or terminus of another entity, such as a route, line, or path.
-
B.
southernmostDistrictOf
Indicates that one district is the geographically furthest south within the boundaries of a specified larger region or entity.
-
C.
liesSoutheastOf
Indicates that one entity is located to the southeast of another, combining both a southern and eastern directional relationship.
-
D.
locatedSouthOf
Indicates that one entity is positioned geographically to the south of another entity.
-
E.
locatedSouthWestOf
Indicates that one entity is positioned to the southwest of another entity, combining both a southern and western relative location.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef62c7a88190851fcd57658b4102 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2eddfb5508190a4e06e1b260d8b2b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.