Triple
T7476665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles T. Schenck |
E176647
|
entity |
| Predicate | leafletsTopic |
P26448
|
FINISHED |
| Object | arguments against the draft |
—
|
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: arguments against the draft | Statement: [Charles T. Schenck, leafletsTopic, arguments against the draft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafletsTopic Context triple: [Charles T. Schenck, leafletsTopic, arguments against the draft]
-
A.
featuresTopic
chosen
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
B.
governedTopic
Indicates that a governing entity exercises authority, control, or regulatory oversight over a particular topic, issue, or domain.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
thematicArea
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
-
E.
legacyTopic
Indicates that a topic or subject is considered outdated, superseded, or retained only for backward compatibility or historical reasons.
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4ee23d081908e05658a651661fc |
completed | March 27, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.