Triple
T30221129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | censor (Roman Republic) |
E768346
|
entity |
| Predicate | couldConveneSenate |
P169374
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [censor (Roman Republic), couldConveneSenate, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: couldConveneSenate Context triple: [censor (Roman Republic), couldConveneSenate, yes]
-
A.
controlledByInSenate
Indicates that one political party or group holds the majority control or leadership over another entity within the context of the Senate.
-
B.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
C.
hasVotingRightInSenate
Indicates that an entity possesses the legal right to participate in voting within a senate body.
-
D.
hasUSSenator
Indicates that a specified state or jurisdiction is represented by a particular individual serving as a United States Senator.
-
E.
hasSenateSeatsSince
Indicates that an entity has held a specified number of seats in a senate starting from a particular point in time.
- 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6801da3e88190a4862f59160e6832 |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 7:35 p.m.