Triple
T13186144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poppy Louise Hager |
E313857
|
entity |
| Predicate | grandfatherPositionHeld |
P979
|
FINISHED |
| Object | 43rd 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: 43rd President of the United States | Statement: [Poppy Louise Hager, grandfatherPositionHeld, 43rd President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandfatherPositionHeld Context triple: [Poppy Louise Hager, grandfatherPositionHeld, 43rd President of the United States]
-
A.
paternalUncleHeldOffice
Indicates that a person’s paternal uncle (their father’s brother) occupied or held a particular office or official position.
-
B.
grandfatherIs
Indicates that one entity is the grandfather (parent of a parent) of another entity.
-
C.
grandfather
chosen
Indicates that one entity is the male parent of another entity’s parent.
-
D.
describesOfficeHeld
Indicates that one entity specifies or characterizes the particular office or position held by another entity.
-
E.
notableFormerOfficeHolderRole
Indicates that an entity previously held a particular official position or role that is considered notable.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:15 p.m.