Triple
T10647224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emer de Vattel |
E250864
|
entity |
| Predicate | primaryWorkSubject |
P40956
|
FINISHED |
| Object | law of nations |
—
|
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: law of nations | Statement: [Emer de Vattel, primaryWorkSubject, law of nations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWorkSubject Context triple: [Emer de Vattel, primaryWorkSubject, law of nations]
-
A.
primaryWork
chosen
Indicates that one work is the main or most significant work associated with a given entity, as opposed to other secondary or related works.
-
B.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
-
D.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
E.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe1cd6081909df9e4dc0fda1f0b |
completed | April 8, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:05 p.m.