Triple
T915662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances Perkins Building |
E19763
|
entity |
| Predicate | namedAfterDistinction |
P63
|
FINISHED |
| Object | first female United States Cabinet member |
—
|
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: first female United States Cabinet member | Statement: [Frances Perkins Building, namedAfterDistinction, first female United States Cabinet member]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterDistinction Context triple: [Frances Perkins Building, namedAfterDistinction, first female United States Cabinet member]
-
A.
namedAfter
chosen
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
B.
namedAfterSince
Indicates that one entity has borne the name of another entity starting from a specific point in time.
-
C.
namedDuring
Indicates that an entity received its name during a specified time period or event.
-
D.
laterNamed
Indicates that an entity was given a new name at a later time, linking its original identity to its subsequent name.
-
E.
hasDistinction
Indicates that one entity possesses, is awarded, or is recognized with a special honor, title, or mark of excellence in relation to another entity or context.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b6755c488190b7f7848110e3ea2c |
completed | March 1, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69a4b292d3408190947cbc2f794cf8c5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.