Triple
T8926315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lex talionis |
E212545
|
entity |
| Predicate | isDefendedFor |
P28479
|
FINISHED |
| Object | clarity of proportional standards |
—
|
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: clarity of proportional standards | Statement: [lex talionis, isDefendedFor, clarity of proportional standards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDefendedFor Context triple: [lex talionis, isDefendedFor, clarity of proportional standards]
-
A.
canBeDefendedIn
chosen
Indicates that something (such as a claim, action, or position) is capable of being justified or supported within a specified context, forum, or framework.
-
B.
defendedAs
Indicates that one entity is presented, argued, or justified as being equivalent to or serving the role of another entity in a defensive or protective context.
-
C.
defenderIn
Indicates that an entity serves as a defensive agent or protector within a specified context, situation, or domain.
-
D.
hasDefenderStrength
Indicates that an entity possesses a certain level or measure of defensive capability or protective power.
-
E.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66700fb48190874563e535f20437 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.