Triple
T664405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Lady of the United States |
E12826
|
entity |
| Predicate | publicPerception |
P17784
|
FINISHED |
| Object | primarily a ceremonial and supportive role |
—
|
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: primarily a ceremonial and supportive role | Statement: [Second Lady of the United States, publicPerception, primarily a ceremonial and supportive role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicPerception Context triple: [Second Lady of the United States, publicPerception, primarily a ceremonial and supportive role]
-
A.
hasPerception
Indicates that one entity is aware of, senses, or recognizes another entity or phenomenon.
-
B.
laterPerception
Indicates that one entity’s perception, awareness, or observation of something occurs after another specified time, event, or perception.
-
C.
visionOf
Indicates that one entity is a visual representation, image, or depiction of another entity.
-
D.
vision
Indicates that an entity perceives another entity or object visually, using sight.
-
E.
primarySense
Indicates that one sense or meaning of an entity is designated as its main or most central sense among possible alternatives.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd3d8fc8190866af5c76c08f486 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d16cff881908c8d2c3fe4d1d6fb |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.