Triple
T3704564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cohens v. Virginia |
E80859
|
entity |
| Predicate | consideredLandmarkFor |
P43158
|
FINISHED |
| Object | development of American federalism |
—
|
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: development of American federalism | Statement: [Cohens v. Virginia, consideredLandmarkFor, development of American federalism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consideredLandmarkFor Context triple: [Cohens v. Virginia, consideredLandmarkFor, development of American federalism]
-
A.
isLandmarkFor
chosen
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
B.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
C.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
D.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
-
E.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54bbfcc8190bec9c16e3749c3b1 |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.