Triple
T847433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Parliament (Strasbourg seat) |
E18306
|
entity |
| Predicate | plenaryChamberCapacity |
P21044
|
FINISHED |
| Object | about 750 seats |
—
|
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: about 750 seats | Statement: [European Parliament (Strasbourg seat), plenaryChamberCapacity, about 750 seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plenaryChamberCapacity Context triple: [European Parliament (Strasbourg seat), plenaryChamberCapacity, about 750 seats]
-
A.
hasPlenaryChamber
Indicates that an institution or governing body possesses a designated plenary chamber where all members can meet and deliberate together.
-
B.
currentRepresentativeChamber
Indicates that an entity currently serves as a representative in a specific legislative chamber.
-
C.
chamberOf
Indicates that one entity is a chamber, room, or enclosed space that is part of, contained within, or assigned to another entity.
-
D.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
E.
clotureThreshold
Indicates the minimum number or proportion of votes required to end debate and proceed to a final decision on a proposal.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac0ba6b4819089c15ed7e1765502 |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa807adc8190ad808a573cf8e923 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4abb157d08190a7d7281eb3f1b788 |
completed | March 1, 2026, 9:12 p.m. |
Created at: March 1, 2026, 7:38 p.m.