Triple
T4609589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfred Pennyworth |
E100521
|
entity |
| Predicate | skills |
P13324
|
FINISHED |
| Object | medicine |
—
|
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: medicine | Statement: [Alfred Pennyworth, skills, medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skills Context triple: [Alfred Pennyworth, skills, medicine]
-
A.
kills
Indicates that one entity causes the death of another entity, ending its life.
-
B.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
-
C.
skillEmphasis
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
D.
competence
chosen
Indicates that an entity has the ability, skill, or qualification to perform a task or fulfill a role effectively.
-
E.
requiresSkill
Indicates that performing or engaging in one entity (e.g., a task or role) depends on possessing or applying a specific skill represented by the other entity.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599f08d88190ad4bed8bafb592cd |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.