Triple
T4113658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viscount Goschen |
E90237
|
entity |
| Predicate | hasHolderOccupation |
P38273
|
FINISHED |
| Object | politician |
—
|
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: politician | Statement: [Viscount Goschen, hasHolderOccupation, politician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHolderOccupation Context triple: [Viscount Goschen, hasHolderOccupation, politician]
-
A.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
B.
holderIs
Indicates that one entity serves as the holder, possessor, or container of another entity.
-
C.
ownerOccupation
chosen
Indicates that the occupation or job role of an entity that owns something is being specified or described.
-
D.
requiredOccupationOf
Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
-
E.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03d7240c8190a64dcbc669772808 |
completed | March 9, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69af0183eb84819087d7184de28f5514 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:41 p.m.