Triple
T2429022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Locri Epizephyrii |
E52798
|
entity |
| Predicate | hasLegalCodeCharacteristic |
P39145
|
FINISHED |
| Object | early codification of laws |
—
|
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: early codification of laws | Statement: [Locri Epizephyrii, hasLegalCodeCharacteristic, early codification of laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalCodeCharacteristic Context triple: [Locri Epizephyrii, hasLegalCodeCharacteristic, early codification of laws]
-
A.
hasLegalFunction
Indicates that an entity performs, fulfills, or is assigned a specific legal role, duty, or function within a legal or regulatory context.
-
B.
usesLegalCode
Indicates that one entity applies, references, or operates under a particular legal code in its actions or regulations.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
-
E.
hasLegalEffect
Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
- F. None of above. chosen
Provenance (4 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcc73d2e48190b6ad5f3ee75b74eb |
completed | March 7, 2026, 6:57 a.m. |
Created at: March 6, 2026, 9:43 p.m.