Triple
T20037857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius A. Wolf |
E497323
|
entity |
| Predicate | laterRelatedCaseYear |
P91150
|
FINISHED |
| Object | 1961 |
—
|
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: 1961 | Statement: [Julius A. Wolf, laterRelatedCaseYear, 1961]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterRelatedCaseYear Context triple: [Julius A. Wolf, laterRelatedCaseYear, 1961]
-
A.
relatedCase
Indicates that one legal case is connected or associated with another case, such as through shared facts, parties, issues, or procedural history.
-
B.
relatedYear
chosen
Indicates a connection between an entity and a specific year that is relevant to its occurrence, validity, or significance.
-
C.
associatedCourtCase
Indicates a relationship where one entity is linked to, or involved in, a particular court case.
-
D.
notableCaseYear
Indicates the year in which a particular case became notable or gained recognized significance.
-
E.
laterRelatedEvent
Indicates that one event is temporally related to another by occurring at a later time.
- 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e935ac8190900cdb4f0cfde505 |
completed | April 20, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:36 p.m.