Triple
T12597668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen for a Day |
E300772
|
entity |
| Predicate | winnerReward |
P14849
|
FINISHED |
| Object | crown and robe |
—
|
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: crown and robe | Statement: [Queen for a Day, winnerReward, crown and robe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerReward Context triple: [Queen for a Day, winnerReward, crown and robe]
-
A.
winnerReceives
chosen
Indicates that the entity identified as the winner is granted or awarded the specified item, benefit, or outcome as a result of winning.
-
B.
winnerMake
Indicates that one entity causes or brings about another entity becoming the winner in a contest, competition, or selection process.
-
C.
winnerManager
Indicates that one entity is the manager or supervisor of another entity who is the winner in a given context or competition.
-
D.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
E.
winnerWork
Indicates that a particular work (such as a book, film, or piece of art) is the one that won a specified award or competition.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9559458dc8190bc4d6e697e99d70e |
completed | April 10, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69d9541894fc8190a0c3706a414279f0 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:08 p.m.