Triple
T4130706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beard |
E85033
|
entity |
| Predicate | associatedWithSkill |
P2830
|
FINISHED |
| Object | prolific scoring |
—
|
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: prolific scoring | Statement: [The Beard, associatedWithSkill, prolific scoring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithSkill Context triple: [The Beard, associatedWithSkill, prolific scoring]
-
A.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
-
B.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
C.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
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.
associatedWithWorkforce
Indicates a relationship in which an entity is connected or related to a particular workforce, such as its members, activities, or management.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:42 p.m.