Triple
T16672300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Out of the Wasteland |
E405133
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Wish |
E596457
|
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: Wish | Statement: [Out of the Wasteland, hasTrack, Wish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wish Context triple: [Out of the Wasteland, hasTrack, Wish]
-
A.
Wish
chosen
"Wish" is an aggressive, industrial rock song by Nine Inch Nails, known for its intense sound and Grammy-winning performance.
-
B.
Wish
Wish is an e-commerce platform and mobile shopping app known for offering a wide variety of low-priced goods shipped directly from merchants, primarily in China, to consumers worldwide.
-
C.
Make a Wish
"Make a Wish" is a 1944 Broadway musical comedy with music and lyrics by Hugh Martin, best known for its lighthearted story and melodic score.
-
D.
Make a Wish
Make a Wish is a short film set in the world of Pixar’s “Inside Out,” expanding on the movie’s exploration of emotions through a new, self-contained story.
-
E.
The Wish List
The Wish List is a young adult fantasy novel by Eoin Colfer that follows a recently deceased teenage girl caught between Heaven and Hell as she attempts to right her past wrongs.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca276848190b7562d7cb88d21e0 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3916508190bd5edd91310ddb5a |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.