Triple
T1893834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctors' Trial |
E41932
|
entity |
| Predicate | numberOfIndictedDefendants |
P26324
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Doctors' Trial, numberOfIndictedDefendants, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIndictedDefendants Context triple: [Doctors' Trial, numberOfIndictedDefendants, 23]
-
A.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
B.
defendantCount
chosen
Indicates the number of defendants involved in a particular legal case or proceeding.
-
C.
notableIndictedLeaders
Indicates that the leaders associated with an entity are notable figures who have been formally indicted on criminal charges.
-
D.
numberOfAcquittals
Indicates the count of instances in which an entity has been formally acquitted of charges or accusations.
-
E.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1497df08190ad90dd89f76208ca |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.