Triple
T8484638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polo Molina |
E200801
|
entity |
| Predicate | hasProfessionalSkill |
P13084
|
FINISHED |
| Object | talent management |
—
|
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: talent management | Statement: [Polo Molina, hasProfessionalSkill, talent management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalSkill Context triple: [Polo Molina, hasProfessionalSkill, talent management]
-
A.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
B.
hasCompetence
chosen
Indicates that an entity possesses the ability, skill, or qualification to perform a specific task or function effectively.
-
C.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
D.
hasProfessionalCore
Indicates that an entity possesses a central set of professional skills, knowledge, or competencies that define its primary professional function or expertise.
-
E.
hasEponymousSkill
Indicates that an entity possesses a skill that is named after a particular person or 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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe539b70c81909f8f045312f0d5f8 |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:12 p.m.