Triple
T6496717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E=MC² |
E148775
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Love Story |
E148870
|
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: Love Story | Statement: [E=MC², hasTrack, Love Story]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Story Context triple: [E=MC², hasTrack, Love Story]
-
A.
Love Story
chosen
"Love Story" is a song by Taylor Swift that became one of her signature hits, blending country and pop influences in a modern retelling of Romeo and Juliet.
-
B.
Love Story
Love Story is a 1944 British romantic drama film starring Margaret Lockwood and Stewart Granger, noted for its wartime setting and emotional love triangle.
-
C.
Sweetheart
"Sweetheart" is a song featured on the album "#1's."
-
D.
The Way We Were
"The Way We Were" is a 1973 romantic drama film starring Barbra Streisand and Robert Redford, renowned for its bittersweet love story and iconic title song.
-
E.
Sea of Love
Sea of Love is a 1989 neo-noir thriller film starring Al Pacino as a New York detective entangled in a dangerous romance while hunting a serial killer.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c68ace80108190804a835bc646b2b2 |
completed | March 27, 2026, 1:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb0988a081909f83af0a9da1b1f1 |
completed | March 27, 2026, 6:23 p.m. |
Created at: March 27, 2026, 1:41 p.m.