Triple
T5403509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States congressional apportionment |
E120835
|
entity |
| Predicate | totalSeatsFixedSince |
P63784
|
FINISHED |
| Object | 1913 |
—
|
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: 1913 | Statement: [United States congressional apportionment, totalSeatsFixedSince, 1913]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSeatsFixedSince Context triple: [United States congressional apportionment, totalSeatsFixedSince, 1913]
-
A.
previousNumberOfSeats
Indicates the number of seats an entity had before a change or update in its seating count.
-
B.
currentNumberOfSeats
Indicates the present total count of seats associated with an entity or context.
-
C.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
D.
numberOfCommonsSeats
Indicates the number of seats an entity holds or is allocated in the House of Commons.
-
E.
numberOfSittings
Indicates the total count of distinct sittings or sessions associated with an entity or event.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8931302c81908afcb0f011e91f09 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:04 p.m.