Triple
T8389924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Flanagan |
E197914
|
entity |
| Predicate | directorOf |
P537
|
FINISHED |
| Object | Hush |
E730771
|
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: Hush | Statement: [Mike Flanagan, directorOf, Hush]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hush Context triple: [Mike Flanagan, directorOf, Hush]
-
A.
Hush
"Hush" is a critically acclaimed, largely dialogue-free horror episode of *Buffy the Vampire Slayer* renowned for its eerie villains, The Gentlemen, and its inventive use of silence.
-
B.
Hush
chosen
Hush is a 2016 horror-thriller film directed and co-written by Mike Flanagan, centered on a deaf-mute woman fighting for survival against a masked killer at her isolated home.
-
C.
Whisper
Whisper is an open-source automatic speech recognition system by OpenAI that transcribes and translates spoken language with high accuracy across many languages.
-
D.
Whisper
Whisper is a feminine hygiene brand of sanitary napkins and related products owned by Procter & Gamble and sold in various international markets.
-
E.
Whispers
Whispers is a bestselling horror-thriller novel by Dean Koontz that blends psychological suspense with supernatural overtones.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb810ac380819095bd67f0555ac2a8 |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce02cb3a1481908d30993d47c70039 |
completed | April 2, 2026, 5:46 a.m. |
Created at: March 30, 2026, 6:03 p.m.