Triple
T30901019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Journey to Justice |
E787166
|
entity |
| Predicate | notableCaseDiscussed |
P99559
|
FINISHED |
| Object | O. J. Simpson murder trial |
E1792692
|
NE 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: O. J. Simpson murder trial | Statement: [Journey to Justice, notableCaseDiscussed, O. J. Simpson murder trial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCaseDiscussed Context triple: [Journey to Justice, notableCaseDiscussed, O. J. Simpson murder trial]
-
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.
notableSupremeCourtCase
Indicates that a legal case is recognized as a significant or influential decision by the Supreme Court.
-
C.
notableCaseArea
Indicates that a particular geographic area is notably associated with, or significantly involved in, a given case or legal matter.
-
D.
notableLawyer
Indicates that the subject is a lawyer who is distinguished or well-known for their legal work or reputation.
-
E.
notableCaseYear
Indicates the year in which a particular case became notable or gained recognized significance.
- F. None of above.
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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a293893f95481908ca455c0d6590b80 |
completed | June 10, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:50 p.m.