Triple
T35790179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Arnold |
E1034671
|
entity |
| Predicate | yearOfPoliticalCampaign |
P82825
|
FINISHED |
| Object | 1962 |
—
|
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: 1962 | Statement: [Kenneth Arnold, yearOfPoliticalCampaign, 1962]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfPoliticalCampaign Context triple: [Kenneth Arnold, yearOfPoliticalCampaign, 1962]
-
A.
yearOfPresidentialCampaign
Indicates the specific year in which an individual conducted or participated in a presidential election campaign.
-
B.
campaignYear
chosen
Indicates the specific year in which a campaign takes place, is launched, or is associated with an entity.
-
C.
senateCampaignYear
Indicates the year in which a given entity’s campaign for a seat in the senate took place.
-
D.
candidacyYear
Indicates the specific year in which an entity is a candidate for a position, office, award, or similar selection process.
-
E.
yearOfPresidentialBid
Indicates the specific year in which an individual made a bid or campaign to become president.
- 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
Created at: May 3, 2026, 4:06 p.m.