Triple
T30164923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eshnunna |
E766768
|
entity |
| Predicate | legalTextLanguage |
P99551
|
FINISHED |
| Object | Akkadian |
—
|
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: Akkadian | Statement: [Eshnunna, legalTextLanguage, Akkadian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalTextLanguage Context triple: [Eshnunna, legalTextLanguage, Akkadian]
-
A.
languageInLaw
Indicates that a specific language is used as the official or operative language within a particular law or legal document.
-
B.
legalContent
Indicates that the associated material complies with applicable laws and regulations and is permitted for use, distribution, or display.
-
C.
languageOfLegalCode
chosen
Indicates that a specified language is the language in which a particular legal code or body of law is written or officially expressed.
-
D.
legalProtectionOfLanguage
Indicates that a language is safeguarded or regulated by formal legal measures, such as laws, policies, or constitutional provisions.
-
E.
legalElement
Indicates that something is a constituent part or component required or recognized within a legal framework, rule, or process.
- 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_69f2247a968881909d79c18f2bfcb275 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: April 29, 2026, 7:23 p.m.