Triple
T14378838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate seat from Maine |
E356545
|
entity |
| Predicate | numberOfIncumbents |
P113810
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [United States Senate seat from Maine, numberOfIncumbents, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIncumbents Context triple: [United States Senate seat from Maine, numberOfIncumbents, 1]
-
A.
hasMultipleIncumbents
Indicates that a given position, role, or office is simultaneously held by more than one incumbent.
-
B.
portionUpForElectionEachCycle
Indicates what fraction of the total membership or seats is contested in each election cycle.
-
C.
incumbentAfterElection
Indicates that an entity holds a position or office as the sitting incumbent following a specified election.
-
D.
incumbentAge
Indicates the age of the current holder of a position or office.
-
E.
lastIncumbent
Indicates that the subject is the most recent person or entity to have held a particular position, office, or role before the current one.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900a67e08190ab1dcf36e6bb3405 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:16 a.m.