Triple
T20389203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Pennsylvania |
E498040
|
entity |
| Predicate | winnerRole |
P139936
|
FINISHED |
| Object | state ambassador |
—
|
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: state ambassador | Statement: [Miss Pennsylvania, winnerRole, state ambassador]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerRole Context triple: [Miss Pennsylvania, winnerRole, state ambassador]
-
A.
winnerState
Indicates the state or condition of an entity that has achieved victory or been declared the winner in a given context.
-
B.
winnerAssociated
Indicates that there is a relevant connection or affiliation between a winner and another entity in the context of a particular event or competition.
-
C.
winnerType
Indicates the category or kind of winner associated with an event, competition, or outcome.
-
D.
winnerManager
Indicates that one entity is the manager or supervisor of another entity who is the winner in a given context or competition.
-
E.
winnerMake
Indicates that one entity causes or brings about another entity becoming the winner in a contest, competition, or selection process.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790d9e5881908bde7da9e5e541a0 |
completed | April 20, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:28 a.m.