Triple
T11471885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The American Boy’s Handy Book |
E271927
|
entity |
| Predicate | targetSkillArea |
P18508
|
FINISHED |
| Object | manual skills |
—
|
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: manual skills | Statement: [The American Boy’s Handy Book, targetSkillArea, manual skills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetSkillArea Context triple: [The American Boy’s Handy Book, targetSkillArea, manual skills]
-
A.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
B.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
-
C.
competenceArea
chosen
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
D.
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.
-
E.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294b3f388190a587c358313f7260 |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.