Triple
T16753596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Wade |
E407150
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | You and Me |
E405134
|
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: You and Me | Statement: [Jason Wade, notableWork, You and Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: You and Me Context triple: [Jason Wade, notableWork, You and Me]
-
A.
You and Me
chosen
"You and Me" is a popular romantic rock ballad by the American band Lifehouse, known for its heartfelt lyrics and widespread radio success in the mid-2000s.
-
B.
You and Me
"You and Me" is a song featured on the soundtrack of the farming simulation video game Harvest Moon.
-
C.
You and Me
"You and Me" is a Soviet drama film by acclaimed director Larisa Shepitko, exploring complex human relationships and moral choices.
-
D.
You and Me
"You and Me" is a component work or project within the interdisciplinary ArtScience initiative, reflecting its blend of artistic creativity and scientific inquiry.
-
E.
You and Me
"You and Me" is a song by La Toya Jackson from her 1988 pop and dance-oriented album "You're Gonna Get Rocked!"
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa28fd3c8190972e2e69ea7dece0 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a525e57881908e9e9453e6d6eb73 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.