Triple
T22034066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trial of the Seventeen |
E544155
|
entity |
| Predicate | hasNumberOfDefendants |
P26324
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [Trial of the Seventeen, hasNumberOfDefendants, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfDefendants Context triple: [Trial of the Seventeen, hasNumberOfDefendants, 17]
-
A.
hasDefendants
Indicates that one or more entities serve as defendants in relation to a particular legal case or proceeding.
-
B.
defendantCount
chosen
Indicates the number of defendants involved in a particular legal case or proceeding.
-
C.
hasNumberOfJurors
Indicates the relationship specifying how many jurors are associated with a given legal case, trial, or proceeding.
-
D.
hasMainDefendant
Indicates that a legal case or proceeding identifies a specific individual or entity as its primary defendant.
-
E.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127ef97348190b8dcdcad11694ebe |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:24 p.m.