Triple
T10163387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porcia gens |
E233945
|
entity |
| Predicate | hasMemberHoldingOffice |
P16080
|
FINISHED |
| Object | censor |
—
|
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: censor | Statement: [Porcia gens, hasMemberHoldingOffice, censor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberHoldingOffice Context triple: [Porcia gens, hasMemberHoldingOffice, censor]
-
A.
memberHoldsOffice
chosen
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
B.
hasMemberByVirtueOfOffice
Indicates that an entity is a member of a group or body specifically because they hold a particular office or position.
-
C.
hasListOfOfficeHolders
Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
-
D.
hasOfficeHolderType
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
E.
hasPresidentialMember
Indicates that an entity includes or is associated with a member who holds or has held the position of president.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec6a7bb48190952f4318af9cc32b |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:09 p.m.