Triple
T3970591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Apple Falls |
E92322
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | Knock Knock |
E92323
|
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: Knock Knock | Statement: [Red Apple Falls, followedBy, Knock Knock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knock Knock Context triple: [Red Apple Falls, followedBy, Knock Knock]
-
A.
Knock Knock
chosen
"Knock Knock" is a prominent work by the artist Smog, known for its introspective, lo-fi indie sound and emotionally resonant songwriting.
-
B.
Knock Knock
"Knock Knock" is a song that appears as the B-side to Monica's single "So Gone."
-
C.
Knock Knock
Knock Knock is a 2015 psychological thriller film directed by Eli Roth, in which Keanu Reeves plays a married man whose life unravels after he lets two mysterious young women into his home.
-
D.
Knick Knack
Knick Knack is a 1989 Pixar animated short film known for its slapstick humor and distinctive 3D computer animation style.
-
E.
Knock
Knock is an Irish village in County Mayo renowned as a major Catholic pilgrimage site following reported Marian apparitions in 1879.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9942c908190aface17a4e8d356d |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5400b75d081909b8e4840b15d19f1 |
completed | March 14, 2026, 11:01 a.m. |
Created at: March 9, 2026, 3:32 p.m.