Triple
T27742373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abgeordnetenhaus of Berlin |
E701887
|
entity |
| Predicate | isLowerOrSingleHouseOf |
P35611
|
FINISHED |
| Object | state legislature of Berlin |
—
|
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: state legislature of Berlin | Statement: [Abgeordnetenhaus of Berlin, isLowerOrSingleHouseOf, state legislature of Berlin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLowerOrSingleHouseOf Context triple: [Abgeordnetenhaus of Berlin, isLowerOrSingleHouseOf, state legislature of Berlin]
-
A.
lowerHouseOf
chosen
Indicates that one entity is the lower chamber in the bicameral legislature of another governing body or jurisdiction.
-
B.
hasLowerHouseSeats
Indicates the number of seats an entity holds in the lower house of a bicameral legislature.
-
C.
lowerHouse
Indicates that one entity functions as the lower chamber of a bicameral legislature in relation to a given political body or system.
-
D.
hasSpeakerInLowerHouse
Indicates that an entity serves as the presiding officer (speaker) of a specified lower house in a bicameral legislature.
-
E.
hasVotingSystemLowerHouse
Indicates that a political entity’s lower legislative chamber uses a specified voting or electoral system.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63717b8c48190abd8ebcc54c76c46 |
completed | May 2, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:12 p.m.