Triple
T16679457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night Train |
E405300
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | My Shadow |
E1226296
|
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: My Shadow | Statement: [Night Train, hasTrack, My Shadow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: My Shadow Context triple: [Night Train, hasTrack, My Shadow]
-
A.
My Shadow
"My Shadow" is a well-known children's poem by Robert Louis Stevenson that playfully explores a child's fascination with their own shadow.
-
B.
My Shadow
chosen
"My Shadow" is a song featured on the "Night Train" EP by the British rock band Keane.
-
C.
Moonlight Shadow
"Moonlight Shadow" is a 1983 pop-rock song by English multi-instrumentalist Mike Oldfield, featuring vocals by Maggie Reilly and known for its melodic guitar work and haunting, narrative lyrics.
-
D.
Moonshadow
"Moonshadow" is a gentle, folk-inspired song by Cat Stevens that reflects on resilience and optimism in the face of life's hardships.
-
E.
Moonshadow
Moonshadow is a critically acclaimed, literary-style science fiction comic series known for its painted artwork and philosophical coming-of-age story, originally published by Epic Comics.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6e74ec81909ea95c3e4b0113ab |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3e2ddc8190a59108cdf001dac2 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.