Triple
T1078053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MFL |
E23882
|
entity |
| Predicate | hasProfessionalRole |
P13957
|
FINISHED |
| Object | MFL teacher |
—
|
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: MFL teacher | Statement: [MFL, hasProfessionalRole, MFL teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalRole Context triple: [MFL, hasProfessionalRole, MFL teacher]
-
A.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
C.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
D.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
E.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b94288d88190aae4fb86236c0702 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.