Triple
T7540936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 104th United States Congress |
E178270
|
entity |
| Predicate | compositionCharacterizedAs |
P662
|
FINISHED |
| Object | divided government at federal level |
—
|
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: divided government at federal level | Statement: [104th United States Congress, compositionCharacterizedAs, divided government at federal level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compositionCharacterizedAs Context triple: [104th United States Congress, compositionCharacterizedAs, divided government at federal level]
-
A.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
B.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
C.
compositionForm
Indicates the structural or organizational form in which something is composed or arranged.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
compositionDetail
Indicates that one entity specifies or describes the internal makeup, structure, or constituent elements of another 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f873b17081908bb70aea0010d072 |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d8eedc81908c1ae421e0e63798 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.