Triple
T20190753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mabel |
E492971
|
entity |
| Predicate | siblingOf |
P363
|
FINISHED |
| Object | Sable |
—
|
NE NERFINISHED |
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: Sable | Statement: [Mabel, siblingOf, Sable]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sable Context triple: [Mabel, siblingOf, Sable]
-
A.
Sable
Sable is a former professional wrestling valet, model, and WWE Diva best known for her prominent role in the WWF/WWE during the late 1990s.
-
B.
Sable
chosen
Sable is a shy, hard-working hedgehog in the Animal Crossing series who runs the Able Sisters tailor shop and gradually opens up to the player through daily conversations.
-
C.
Tigern
Tigern was a warship that took part in the early 17th-century naval Battle of Oliwa between the Polish–Lithuanian Commonwealth and Sweden.
-
D.
Biard
Biard is a commune in western France, near the city of Poitiers, known for hosting the regional Poitiers–Biard Airport.
-
E.
Badger
Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad593f88190a1e534fed38b3cd7 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.