Triple
T514433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trial of the Sixteen |
E10674
|
entity |
| Predicate | defendantsCount |
P866
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Trial of the Sixteen, defendantsCount, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defendantsCount Context triple: [Trial of the Sixteen, defendantsCount, 16]
-
A.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
B.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
C.
numberOfPeopleAccused
chosen
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
D.
numberOfCourts
Indicates the quantity of courts associated with or present at a given entity or location.
-
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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f232fa688190b08a2fe3f22c7a6e |
completed | Feb. 28, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69a2f013c05481909e6dc87e7b20ebd8 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.