Triple
T21187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twenty-second Amendment to the United States Constitution |
E420
|
entity |
| Predicate | hasSectionCount |
P1632
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Twenty-second Amendment to the United States Constitution, hasSectionCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionCount Context triple: [Twenty-second Amendment to the United States Constitution, hasSectionCount, 2]
-
A.
hasSectionKnownAs
Indicates that an entity includes a section or part that is referred to by a specific name.
-
B.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
-
C.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
D.
hasCollection
Indicates that an entity possesses, maintains, or is associated with a set or group of related items treated as a collection.
-
E.
hasPlurality
Indicates that an entity or concept exists or is expressed in a plural form rather than a singular one.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246f4d7908190a947f6da251c6f3b |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.