Triple
T8671941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'm Wide Awake, It's Morning |
E205816
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Train Under Water |
E750192
|
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: Train Under Water | Statement: [I'm Wide Awake, It's Morning, hasSingle, Train Under Water]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Train Under Water Context triple: [I'm Wide Awake, It's Morning, hasSingle, Train Under Water]
-
A.
Train Under Water
chosen
"Train Under Water" is a song by the American indie rock band Bright Eyes from their 2005 album "I'm Wide Awake, It's Morning."
-
B.
"Underwater"
"Underwater" is a song by Finnish singer-songwriter Mika known for its emotive vocals and lush, dramatic pop production.
-
C.
Underwater
Underwater is a 2020 science fiction horror film starring Kristen Stewart as a mechanical engineer struggling to survive after an earthquake devastates a deep-sea research facility.
-
D.
Deep Sea
Deep Sea is an aquarium exhibit showcasing the mysterious life forms and extreme environments found in the ocean’s deepest regions.
-
E.
Down in the Depths
"Down in the Depths" is a classic Cole Porter torch song, best known through jazz and pop vocal interpretations such as Ella Fitzgerald’s.
- 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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc491a34d08190b0795079d192a03d |
completed | March 31, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3960ce881908f07fb9fdafcd550 |
completed | April 2, 2026, 10:54 p.m. |
Created at: March 30, 2026, 6:31 p.m.