Triple
T12350038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tears of a Clown |
E294458
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | Make It Happen |
E142015
|
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: Make It Happen | Statement: [The Tears of a Clown, album, Make It Happen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Make It Happen Context triple: [The Tears of a Clown, album, Make It Happen]
-
A.
Make It Happen
chosen
"Make It Happen" is a song featured on the album *Emotions* by Mariah Carey.
-
B.
Let It Happen
"Let It Happen" is a track by Greek composer Vangelis featured on his 1979 electronic music album "Earth."
-
C.
Let It Happen
"Let It Happen" is a critically acclaimed psychedelic synth-pop track by Tame Impala, known for its sprawling, hypnotic production and exploration of surrendering to change.
-
D.
You Can Make It Happen
"You Can Make It Happen" is a self-help and personal development book by Stedman Graham that focuses on building self-awareness, setting goals, and taking responsibility to achieve success.
-
E.
Making It
Making It is an American television series best known as a lighthearted crafting competition show co-hosted by Amy Poehler and Nick Offerman.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7cbff08190849cd2aec4ce3243 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ab066108190bba8eca95d3e0a81 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.