Triple
T16704360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg IG Farben trial |
E405925
|
entity |
| Predicate | numberOfMistrialsOrUntried |
P124302
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Nuremberg IG Farben trial, numberOfMistrialsOrUntried, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMistrialsOrUntried Context triple: [Nuremberg IG Farben trial, numberOfMistrialsOrUntried, 1]
-
A.
numberOfNoContests
Indicates the total count of events, matches, or decisions that were recorded as "no contest" rather than a win, loss, or draw.
-
B.
unsuccessfullyContested
Indicates that an attempt was made to challenge or dispute something, but the challenge did not succeed.
-
C.
numberOfPeopleTried
Indicates the count of distinct people who have attempted or tried a particular action, task, or item.
-
D.
numberOfAcquittals
Indicates the count of instances in which an entity has been formally acquitted of charges or accusations.
-
E.
numberOfSuffetes
Indicates the relationship specifying how many suffetes (joint magistrates or chief officials) are associated with a given entity or context.
- F. None of above. chosen
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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3833496dc8190ae4b4a03ba04d69d |
completed | April 18, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.