Triple
T15959072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wade Watts |
E387010
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Wade Owen Watts |
E387010
|
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: Wade Owen Watts | Statement: [Wade Watts, fullName, Wade Owen Watts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wade Owen Watts Context triple: [Wade Watts, fullName, Wade Owen Watts]
-
A.
Wade Watts
chosen
Wade Watts is the teenage protagonist of Ernest Cline's science-fiction novel "Ready Player One," known for his quest through the virtual reality world of the OASIS to solve an elaborate pop-culture–laden Easter egg hunt.
-
B.
Nathan Darrow
Nathan Darrow is an American actor best known for his roles in the television series "House of Cards" and "Gotham."
-
C.
Evan Weiss
Evan Weiss is a television writer and producer best known for creating the 1990s sitcom *The Sinbad Show*.
-
D.
Gabriel Rhodes
Gabriel Rhodes is a film editor known for his work on the documentary "Parkland."
-
E.
Sid Sawyer
Sid Sawyer is Tom Sawyer’s well-behaved but tattling half-brother in Mark Twain’s classic novel "The Adventures of Tom Sawyer."
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fe82d081908b5d41bc5a709de2 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe806ef4819095a4dfe104d0bdc8 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.