Triple
T30164924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eshnunna |
E766768
|
entity |
| Predicate | legalTextScript |
P133837
|
FINISHED |
| Object | cuneiform |
—
|
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: cuneiform | Statement: [Eshnunna, legalTextScript, cuneiform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalTextScript Context triple: [Eshnunna, legalTextScript, cuneiform]
-
A.
legalContent
Indicates that the associated material complies with applicable laws and regulations and is permitted for use, distribution, or display.
-
B.
legalElement
Indicates that something is a constituent part or component required or recognized within a legal framework, rule, or process.
-
C.
scriptInLaw
chosen
Indicates that a particular writing system or script is used within the text of a legal document or law.
-
D.
legalTool
Indicates a relationship where something functions as a legal instrument, mechanism, or means used to achieve or regulate a legal purpose or outcome.
-
E.
legalPretext
Indicates that an action or decision is justified using a stated legal reason that serves as a cover for a different, underlying motive.
- 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_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: April 29, 2026, 7:23 p.m.