Triple
T16439450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wildness |
E399259
|
entity |
| Predicate | thirdSingle |
P25309
|
FINISHED |
| Object | Empress |
E321906
|
NE 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: Empress | Statement: [Wildness, thirdSingle, Empress]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Empress Context triple: [Wildness, thirdSingle, Empress]
-
A.
Empress
chosen
Empress is a studio album by Nigerian singer Yemi Alade that showcases her Afro-pop sound and themes of female empowerment.
-
B.
Empress
Empress was the radio callsign used by Canadian Pacific Air Lines for its commercial flight operations.
-
C.
Empress
Empress is a science fiction comic book series written by Mark Millar that follows a queen fleeing a tyrannical galactic emperor with her children across the universe.
-
D.
Empress
Empress is the title given to the principal wife or female counterpart of an emperor, often serving as the highest-ranking woman in an imperial court.
-
E.
Empress Tudan
Empress Tudan was a consort of Emperor Zhangzong of the Jurchen-led Jin dynasty in China, holding the title of empress during his reign.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba720a48190b0b412225e993e52 |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00458dde8881909778c9964ddc8efa |
completed | May 10, 2026, 8:45 a.m. |
Created at: April 10, 2026, 5:10 a.m.