Triple
T4654451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don't Fall in Love with a Dreamer |
E102373
|
entity |
| Predicate | isMajorCrossoverHit |
P56239
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Don't Fall in Love with a Dreamer, isMajorCrossoverHit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMajorCrossoverHit Context triple: [Don't Fall in Love with a Dreamer, isMajorCrossoverHit, true]
-
A.
crossoverHit
chosen
Indicates that a creative work has achieved significant popularity or success across multiple distinct audience segments, genres, or markets beyond its original target.
-
B.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
C.
hasCrossoverHits
Indicates that an entity (such as an artist or work) has achieved significant success across multiple distinct genres, markets, or audience categories.
-
D.
isMajorInterchangeFor
Indicates that one location functions as a primary hub where multiple routes or lines connect or transfer between each other for another location.
-
E.
isMajor
Indicates that an entity holds primary or greater significance, importance, or rank relative to others in a given context.
- F. None of above.
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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd631623d881908a59dafa7702af54 |
completed | March 20, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69bd62126b0c81909ba3f21b21e30d54 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:14 p.m.