Triple
T132114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judiciary Act of 1789 |
E2674
|
entity |
| Predicate | definedNumberOfAssociateJustices |
P6910
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Judiciary Act of 1789, definedNumberOfAssociateJustices, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definedNumberOfAssociateJustices Context triple: [Judiciary Act of 1789, definedNumberOfAssociateJustices, 5]
-
A.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
B.
chiefJustice
Indicates that one entity serves as the chief justice (the highest-ranking judicial officer) of another entity, such as a court or jurisdiction.
-
C.
chiefJusticeSinceYear
Indicates that an entity has held the position of chief justice starting from a specified year.
-
D.
hasConcurringJustice
Indicates that a judicial decision is associated with a justice who wrote or joined a concurring opinion.
-
E.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25855baf48190a1b63f2e5865d957 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2564edb488190974dc00eb9ac37d9 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2585408c881908a25b5c61f300154 |
completed | Feb. 28, 2026, 2:52 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.