Triple
T6330571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip K. Dick |
E141969
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Paycheck |
E582867
|
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: Paycheck | Statement: [Philip K. Dick, notableWork, Paycheck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paycheck Context triple: [Philip K. Dick, notableWork, Paycheck]
-
A.
Paycheck
chosen
Paycheck is a 2003 science fiction action thriller film, based on a Philip K. Dick short story, about an engineer who must piece together his erased memories to uncover a conspiracy.
-
B.
Payday
Payday is a 1973 American drama film starring Rip Torn as a hard-living country singer whose self-destructive lifestyle unravels over the course of a few chaotic days.
-
C.
Payday
"Payday" is a song by the American rock band Culture, recognized as one of their notable musical works.
-
D.
Paycom
Paycom is a U.S.-based software company that provides cloud-based payroll and human capital management solutions to businesses.
-
E.
Payback
Payback is a 1999 neo-noir crime film starring Mel Gibson as a vengeful thief seeking repayment after being double-crossed.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06514cbe8819096dbeb17ccb3e3d5 |
completed | March 22, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6041aac948190ad7dd4d5683903ed |
completed | March 27, 2026, 4:14 a.m. |
Created at: March 22, 2026, 4:30 p.m.