Triple
T14485185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Colston |
E359208
|
entity |
| Predicate | adultProfession |
P100365
|
FINISHED |
| Object | retired civil servant (implied) |
—
|
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: retired civil servant (implied) | Statement: [Leo Colston, adultProfession, retired civil servant (implied)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adultProfession Context triple: [Leo Colston, adultProfession, retired civil servant (implied)]
-
A.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
B.
leftProfession
Indicates that an entity has stopped or abandoned a particular profession or occupation they previously held.
-
C.
professionalHead
Indicates that one entity serves as the primary professional leader or chief authority over another entity within an organizational or occupational context.
-
D.
professionalClass
chosen
Indicates that an entity belongs to, or is categorized within, a particular professional or occupational class.
-
E.
professionalBody
Indicates that an entity is a formal organization that represents, regulates, or supports members of a particular profession.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924d7f4c8190b1f62b5ffe1ff649 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.