Triple
T17232179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Only in the Movies |
E418268
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Only in the Movies |
E418268
|
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: Only in the Movies | Statement: [Only in the Movies, hasTitle, Only in the Movies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Only in the Movies Context triple: [Only in the Movies, hasTitle, Only in the Movies]
-
A.
Only in the Movies
chosen
"Only in the Movies" is a song featured in the musical adaptation of "Kiss of the Spider Woman."
-
B.
The Movies
The Movies is a simulation video game that lets players run a Hollywood film studio, managing production, stars, and the creation of custom movies.
-
C.
Living at the Movies
Living at the Movies is a poetry collection by American writer and punk icon Jim Carroll, known for its vivid, streetwise depictions of urban life and youth.
-
D.
Movies!
Movies! is an American digital multicast television network specializing in classic and older feature films, typically airing uncut and in their original aspect ratios.
-
E.
Film Begets Film
Film Begets Film is a critical study by film historian Jay Leyda that examines the influence of existing films on the creation and evolution of new cinematic works.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42df7da748190a3a1762a67eb871b |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a016760873c8190bab70ad4ca0c6d8e |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:39 a.m.