Triple
T7376308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paulus |
E170131
|
entity |
| Predicate | legalWritingsCharacterizedAs |
P61937
|
FINISHED |
| Object | authoritative |
—
|
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: authoritative | Statement: [Paulus, legalWritingsCharacterizedAs, authoritative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalWritingsCharacterizedAs Context triple: [Paulus, legalWritingsCharacterizedAs, authoritative]
-
A.
legalCharacterization
Indicates how an action, event, or situation is classified or characterized under a specific legal framework or set of laws.
-
B.
lawCharacteristicInText
chosen
Indicates that a specific legal characteristic or feature is expressed, described, or referenced within a given text.
-
C.
legalTextTypeWorkedOn
Indicates that an entity has worked on or handled a specific type or category of legal text.
-
D.
legalReformer
Indicates that an entity works to change, improve, or modernize laws or legal systems.
-
E.
legalRepresentation
Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a8b18c8190ad1a19521eda2319 |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:07 p.m.