Triple
T18233159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Side Effects of You |
E436595
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lose to Win |
—
|
NE NERFINISHED |
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: Lose to Win | Statement: [Side Effects of You, hasPart, Lose to Win]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lose to Win Context triple: [Side Effects of You, hasPart, Lose to Win]
-
A.
Lose to Win
chosen
"Lose to Win" is an R&B song by American singer Fantasia Barrino that reflects on overcoming hardship and personal struggle in relationships.
-
B.
Win Some, Lose Some
"Win Some, Lose Some" is a reflective hip-hop track by Big Sean that explores personal struggles, growth, and the costs of success.
-
C.
Win, Lose or Die
"Win, Lose or Die" is a James Bond novel by British author John Gardner that follows 007 as he tackles a high-stakes terrorist plot involving NATO and global security.
-
D.
Win Some Lose Some
"Win Some Lose Some" is a song by British pop artist Robbie Williams, released as part of his successful early solo work.
-
E.
Tell to Win
"Tell to Win" is a business and leadership book by Hollywood executive Peter Guber that explains how strategic storytelling can be used to persuade, inspire, and drive success.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b512a88190aa493b0793ab28b3 |
completed | April 19, 2026, 3:28 p.m. |
Created at: April 10, 2026, 10:33 a.m.