Triple
T12150264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothy Arnold |
E289432
|
entity |
| Predicate | notableCaseType |
P99559
|
FINISHED |
| Object | early 20th-century urban disappearance |
—
|
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: early 20th-century urban disappearance | Statement: [Dorothy Arnold, notableCaseType, early 20th-century urban disappearance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCaseType Context triple: [Dorothy Arnold, notableCaseType, early 20th-century urban disappearance]
-
A.
notableCaseContext
chosen
Indicates that an entity is associated with a particular contextual detail, circumstance, or background information relevant to a notable case or instance.
-
B.
notableCaseArea
Indicates that a particular geographic area is notably associated with, or significantly involved in, a given case or legal matter.
-
C.
notableSupremeCourtCase
Indicates that a legal case is recognized as a significant or influential decision by the Supreme Court.
-
D.
notableCaseYear
Indicates the year in which a particular case became notable or gained recognized significance.
-
E.
notableCourt
Indicates that a particular court is especially significant 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.