Triple
T38498490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Artis |
E919759
|
entity |
| Predicate | legalOutcomeYear |
P159393
|
FINISHED |
| Object | 1985 |
—
|
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: 1985 | Statement: [John Artis, legalOutcomeYear, 1985]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalOutcomeYear Context triple: [John Artis, legalOutcomeYear, 1985]
-
A.
legalCaseHeParticipatedInDecisionYear
Indicates the year in which he participated in making the decision in a particular legal case.
-
B.
legalOutcome
Indicates the resulting legal status, decision, or consequence that follows from a legal process, action, or judgment.
-
C.
lawsuitYear
Indicates the calendar year in which a lawsuit was filed, initiated, or formally recorded.
-
D.
lawsuitSettlementYear
chosen
Indicates the year in which a lawsuit between parties was formally settled or resolved.
-
E.
legalCaseOutcomeAssociatedWith
Indicates that a particular legal case outcome is connected or linked to a specific related entity, such as a case, party, or legal proceeding.
- 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_69f76e9ddd4481908f8c04439d848f9d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00372ff0e48190b3ed91f9bae9da6c |
completed | May 10, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_6a00359c1b8481909c1e43df9f5a789a |
completed | May 10, 2026, 7:37 a.m. |
Created at: May 3, 2026, 4:31 p.m.