Triple
T34831612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morrill Tariff |
E1004078
|
entity |
| Predicate | regionOpposed |
P167040
|
FINISHED |
| Object | Southern United States |
—
|
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: Southern United States | Statement: [Morrill Tariff, regionOpposed, Southern United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOpposed Context triple: [Morrill Tariff, regionOpposed, Southern United States]
-
A.
regionOpposedExpansionIn
Indicates that a region actively resisted or opposed the expansion of another entity into its territory or sphere of influence.
-
B.
regionOfStrongOpposition
chosen
Indicates that one entity is a geographic or conceptual area where there is significant resistance or disagreement toward another entity or its actions.
-
C.
positionOpposed
Indicates that two entities hold positions or stances that are in direct conflict or opposition to each other.
-
D.
opposingLocation
Indicates that two entities are located directly opposite each other, typically across a defined reference such as a street, corridor, or boundary.
-
E.
opposedDirectionRegion
Indicates that one region is oriented in the exact opposite direction relative to another region.
- 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_69f76db7d1b4819093bd4912d80d845d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff97637ad881908c24fe2cc6b036db |
completed | May 9, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69ff96c43a808190942eeda1934602db |
completed | May 9, 2026, 8:19 p.m. |
Created at: May 3, 2026, 4 p.m.