Triple
T9422893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salian Franks |
E227197
|
entity |
| Predicate | lawFeature |
P25070
|
FINISHED |
| Object | agnatic succession emphasized in Salic law |
—
|
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: agnatic succession emphasized in Salic law | Statement: [Salian Franks, lawFeature, agnatic succession emphasized in Salic law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawFeature Context triple: [Salian Franks, lawFeature, agnatic succession emphasized in Salic law]
-
A.
featuresLaw
Indicates that something includes, presents, or is characterized by a particular law or legal provision.
-
B.
lawLibrary
Indicates a relationship where a location or resource functions as a library specifically dedicated to legal materials, services, or research.
-
C.
legalSystemFeature
chosen
Indicates a characteristic, rule, or structural element that forms part of a particular legal system.
-
D.
lawCharacteristicInText
Indicates that a specific legal characteristic or feature is expressed, described, or referenced within a given text.
-
E.
lawJournal
Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c27c8cc8190a11162c10c33b17e |
completed | April 1, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.