Triple
T19323847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FrontRunner |
E483294
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Sandy |
—
|
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: Sandy | Statement: [FrontRunner, servesCity, Sandy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandy Context triple: [FrontRunner, servesCity, Sandy]
-
A.
Sandy
Sandy is the commonly used nickname of Sandy Brondello, an Australian former professional basketball player and current WNBA head coach.
-
B.
Sandy
Sandy is a central female character in the 1971 film "Carnal Knowledge," representing one of the key romantic relationships that illuminate the protagonists’ evolving attitudes toward sex and intimacy.
-
C.
Sandy
Sandy is a common nickname or short form of the given name Alexander.
-
D.
Sandy
Sandy is a fictional character from Mark Twain’s satirical novel "A Connecticut Yankee in King Arthur’s Court," known as a medieval woman who becomes the companion and later wife of the time-traveling protagonist.
-
E.
Sandy
chosen
Sandy is a suburban city in the Salt Lake City metropolitan area of Utah, known for its residential communities and proximity to outdoor recreation in the nearby Wasatch Mountains.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8a07508190a2e5f8972d1efba0 |
completed | April 20, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:32 p.m.