Triple
T33842344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manikay |
E867388
|
entity |
| Predicate | hasRelationToLaw |
P142158
|
FINISHED |
| Object | embodiment of Yolngu 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: embodiment of Yolngu law | Statement: [Manikay, hasRelationToLaw, embodiment of Yolngu law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationToLaw Context triple: [Manikay, hasRelationToLaw, embodiment of Yolngu law]
-
A.
hasRelationshipToLaw
chosen
Indicates that one entity has a defined connection, relevance, or applicability to a specific law or legal framework.
-
B.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
C.
containsLaw
Indicates that one entity (such as a document, code, or jurisdiction) includes or encompasses a specific law within it.
-
D.
relationshipToStateLaw
Indicates how something is connected or subject to the provisions, requirements, or authority of a particular state law.
-
E.
hasJurisprudence
Indicates a relationship where an entity possesses, is associated with, or is governed by a particular body of legal principles, case law, or judicial doctrine.
- 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:47 a.m.