Triple
T30123336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lentulus |
E765616
|
entity |
| Predicate | bearersBelongedTo |
P176331
|
FINISHED |
| Object | Roman Senate |
—
|
NE NERFINISHED |
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: Roman Senate | Statement: [Lentulus, bearersBelongedTo, Roman Senate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearersBelongedTo Context triple: [Lentulus, bearersBelongedTo, Roman Senate]
-
A.
typicalBearers
Indicates that certain entities are the usual or characteristic holders, users, or possessors of a given property, role, or attribute.
-
B.
bearerByname
Indicates that an entity is known or referred to by a particular byname or secondary name.
-
C.
believedToBelongTo
Indicates that something is thought or assumed, but not definitively known, to be owned by or part of a particular entity.
-
D.
typicalNameBearers
Indicates that the subject is a common or characteristic name borne by the entities in the object set.
-
E.
typicalBearersNationality
Indicates the nationality that entities of a given type or class are most commonly associated with.
- F. None of above. chosen
Provenance (4 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6dfcafd0c81908d86662948c539d6 |
completed | May 3, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6df418f488190a5e7ff41f32dceda |
completed | May 3, 2026, 5:38 a.m. |
Created at: April 29, 2026, 7:13 p.m.