Triple
T9368008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Came to the City |
E225456
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Michael from Mountains |
E225459
|
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: Michael from Mountains | Statement: [I Came to the City, hasTrack, Michael from Mountains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael from Mountains Context triple: [I Came to the City, hasTrack, Michael from Mountains]
-
A.
Michael from Mountains
chosen
"Michael from Mountains" is a folk-inspired song by Joni Mitchell, featured on her 1968 debut album "Song to a Seagull."
-
B.
Mikey Welsh
Mikey Welsh was an American bassist and visual artist best known for his tenure with the rock band Weezer in the late 1990s and early 2000s.
-
C.
Michael’s
Michael’s is a national arts and crafts retail chain known for selling hobby supplies, home décor, and DIY project materials.
-
D.
Mychael
Mychael is a Canadian film composer best known for his evocative, world music–influenced scores, including the Academy Award–winning soundtrack for "Life of Pi."
-
E.
Blake Michael
Blake Michael is an American actor and musician best known for his role in the Disney Channel film "Lemonade Mouth."
- 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd507f9ed8819092967b204faa4408 |
completed | April 1, 2026, 5:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0f4010ea88190b056f57bab78bef9 |
completed | April 4, 2026, 11:20 a.m. |
Created at: March 30, 2026, 7:43 p.m.