Triple
T15114069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | family de Bombelles |
E360989
|
entity |
| Predicate | hasMemberInProfession |
P112780
|
FINISHED |
| Object | diplomats |
—
|
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: diplomats | Statement: [family de Bombelles, hasMemberInProfession, diplomats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberInProfession Context triple: [family de Bombelles, hasMemberInProfession, diplomats]
-
A.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
B.
hasMemberWhoHeldOccupation
chosen
Indicates that a group or collective entity includes at least one member who has held a specified occupation.
-
C.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
-
D.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
E.
hasChildInSameProfession
Indicates that an individual has at least one child whose profession is the same as their own.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058f4fb88190a3d446a466aebcf1 |
completed | April 15, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:05 a.m.