Triple
T2841874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alf Landon |
E62487
|
entity |
| Predicate | ran for office |
P355
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [Alf Landon, ran for office, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ran for office Context triple: [Alf Landon, ran for office, President of the United States]
-
A.
ranForOffice
chosen
Indicates that an entity was a candidate seeking election to a public or organizational office.
-
B.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
C.
reorganizedOfficeOf
Indicates that one entity has restructured, reshaped, or otherwise reorganized the organizational structure or functions of another entity’s office.
-
D.
runsFrom
Indicates that one entity flees or escapes away from another entity.
-
E.
portraysOffice
Indicates that one entity depicts, represents, or shows an office (as a place, role, or position) associated with another entity.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf16d0c08190bb8de4a4160b4414 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.