Triple
T17171604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stark Sands |
E416747
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sands |
E1044049
|
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: Sands | Statement: [Stark Sands, familyName, Sands]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sands Context triple: [Stark Sands, familyName, Sands]
-
A.
Sands
chosen
Sands is a surname most notably associated with English actor Julian Sands, known for his roles in films such as "A Room with a View" and "Warlock."
-
B.
Sands
Sands is a ruthless, manipulative CIA agent portrayed by Johnny Depp in the action film "Once Upon a Time in Mexico."
-
C.
Sands
Sands is a global casino and resort brand best known for its luxury integrated resorts and gaming properties, particularly in Las Vegas and Macao.
-
D.
Sunny Sands
Sunny Sands is a popular sandy beach in Folkestone, Kent, known for its family-friendly atmosphere and traditional seaside charm.
-
E.
Sea of Sand
The Sea of Sand is a vast, otherworldly volcanic sand plain surrounding Mount Bromo in East Java, Indonesia, renowned for its stark, lunar-like landscape.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0ac22481909e992bb3a6ba36ad |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01483f85648190acaeb197013e1f1b |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.