Triple
T17909691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mordecai |
E447787
|
entity |
| Predicate | hasJobRole |
P44925
|
FINISHED |
| Object | park groundskeeper |
—
|
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: park groundskeeper | Statement: [Mordecai, hasJobRole, park groundskeeper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJobRole Context triple: [Mordecai, hasJobRole, park groundskeeper]
-
A.
hasIndustryRole
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
-
B.
employedRole
chosen
Indicates that an entity holds or performs a specific role or position within an employment or work context.
-
C.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
D.
hasProductionRole
Indicates that an entity holds a specific role or function in the production or creation process of another entity.
-
E.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9f4f888190840c8b55672becf8 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:19 a.m.