Triple
T26888819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Nixon |
E677116
|
entity |
| Predicate | hasRelativeWhoWas |
P367
|
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: [Donald Nixon, hasRelativeWhoWas, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeWhoWas Context triple: [Donald Nixon, hasRelativeWhoWas, President of the United States]
-
A.
hadRelative
Indicates that one entity had a familial relationship with another entity.
-
B.
hasGenealogicalRelation
Indicates that there exists a family or ancestry-based relationship (such as parent, child, sibling, or more distant kinship) between the related entities.
-
C.
appointedRelative
Indicates that one entity has formally assigned or designated another entity, who is a relative, to a specific role, position, or responsibility.
-
D.
notableRelative
chosen
Indicates that an entity has a relative who is notable or well-known, specifying that familial relationship.
-
E.
hasBiographicalRelation
Indicates a relationship where one entity has a biographical connection to another, such as being the subject, author, or source of biographical information.
- 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_69eee9bc0c90819085608c8bdc513a57 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fe349879848190bcd77e3cc3470458 |
completed | May 8, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69fe31e3cf908190b23ebc2f7fe58722 |
completed | May 8, 2026, 6:56 p.m. |
Created at: April 27, 2026, 5:43 a.m.