Triple
T5058475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cain |
E113963
|
entity |
| Predicate | markPurpose |
P79
|
FINISHED |
| Object | protection from being killed |
—
|
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: protection from being killed | Statement: [Cain, markPurpose, protection from being killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: markPurpose Context triple: [Cain, markPurpose, protection from being killed]
-
A.
purpose
chosen
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
B.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
C.
accessPurpose
Indicates that one entity uses or accesses another entity specifically for a defined purpose or intended use.
-
D.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
E.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74523434819092b8b15992073b5b |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.