Triple
T13795997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shay Hatten |
E331513
|
entity |
| Predicate | wroteScreenplayFor |
P15305
|
FINISHED |
| Object | Day Shift |
E1062960
|
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: Day Shift | Statement: [Shay Hatten, wroteScreenplayFor, Day Shift]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Day Shift Context triple: [Shay Hatten, wroteScreenplayFor, Day Shift]
-
A.
Day Shift
chosen
Day Shift is a 2022 action-comedy vampire film starring Jamie Foxx as a blue-collar dad who secretly works as a vampire hunter in Los Angeles.
-
B.
Night Shift
Night Shift is a 1982 comedy film directed by Ron Howard that helped establish Michael Keaton as a major comedic actor.
-
C.
Night Shift
"Night Shift" is a critically acclaimed indie rock song by American singer-songwriter Lucy Dacus, known for its emotionally raw lyrics and slow-building, cathartic arrangement.
-
D.
Night Shift
"Night Shift" is a 1978 collection of horror and suspense short stories by Stephen King that helped establish his reputation as a master of the genre.
-
E.
Third Shift
Third Shift is a beer brand produced by MillerCoors, positioned as a craft-style lager inspired by small-batch brewing traditions.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025be1f08190aac525d72d7dc0c3 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8d893448190b37ecbf8d2ded239 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:11 p.m.