Triple
T8910559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Lynn |
E212170
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | We’ll Meet Again |
E507804
|
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: We’ll Meet Again | Statement: [Vera Lynn, notableWork, We’ll Meet Again]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: We’ll Meet Again Context triple: [Vera Lynn, notableWork, We’ll Meet Again]
-
A.
We’ll Meet Again
chosen
"We’ll Meet Again" is a famous World War II–era song, popularized by British singer Vera Lynn, that became an emblematic anthem of hope and reunion during wartime separation.
-
B.
You and I Will Meet Again
"You and I Will Meet Again" is a song by Tom Petty and the Heartbreakers from their 1991 album *Into the Great Wide Open*.
-
C.
Meet Me in the Morning
"Meet Me in the Morning" is a blues-infused song by Bob Dylan, featured on his acclaimed 1975 album Blood on the Tracks.
-
D.
I’ll Be Seeing You
"I’ll Be Seeing You" is a 1944 American romantic drama film, noted for its wartime setting and poignant story of two troubled strangers who meet and fall in love over the Christmas holidays.
-
E.
I’ll Be Seeing You
"I’ll Be Seeing You" is a suspense novel by Mary Higgins Clark that follows a television reporter drawn into a dangerous mystery after recognizing her own face on a missing woman’s body.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc65227d008190b13ba162d0b3c9d1 |
completed | April 1, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba36f8cc8190ab57ddc99b7219d1 |
completed | April 3, 2026, 1:01 p.m. |
Created at: March 30, 2026, 6:55 p.m.