Triple
T2399733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Lou Retton |
E47737
|
entity |
| Predicate | wasFlagBearer |
P4357
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mary Lou Retton, wasFlagBearer, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasFlagBearer Context triple: [Mary Lou Retton, wasFlagBearer, yes]
-
A.
flagBearer
chosen
Indicates that one entity serves as the carrier or holder of a flag on behalf of another entity, group, or cause.
-
B.
flagBearerState
Indicates that a state serves as the flag-bearing entity (e.g., the country whose flag is being represented) in relation to another entity or context.
-
C.
flagFlown
Indicates that a particular flag is being displayed or flown at a specific location or by a specific entity.
-
D.
hasFlagstaff
Indicates that one entity possesses, contains, or is equipped with a flagstaff (a pole or staff for displaying a flag).
-
E.
flagshipFor
Indicates that one entity serves as the primary or leading representative example for another entity, often embodying its most important qualities or status.
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc8c95d8c819088e4bb4fb32452ae |
completed | March 7, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69abc5a3825c81909ec6111dfc165453 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.