Triple
T12992666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia congressional delegation |
E321953
|
entity |
| Predicate | houseSeatsApportioned |
P4273
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Georgia congressional delegation, houseSeatsApportioned, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: houseSeatsApportioned Context triple: [Georgia congressional delegation, houseSeatsApportioned, 14]
-
A.
apportionedBy
Indicates that something is divided or allocated among parts or recipients according to a specified agent, rule, or method.
-
B.
numberOfRepresentatives
chosen
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
firstCongressionalApportionment
Indicates the initial allocation of legislative representation (such as seats in a congress or parliament) among regions or constituencies following the first relevant census or founding arrangement.
-
D.
parliamentarySeats
Indicates the number of seats a party, group, or representative holds in a parliamentary body.
-
E.
firstApportionedUnderCurrentSystem
Indicates that something was initially allocated or distributed under the rules of the current system in use.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:44 p.m.