Triple
T16875697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Lockwood |
E421292
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Love Story |
E457417
|
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: [Margaret Lockwood, notableWork, Love Story]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Story Context triple: [Margaret Lockwood, notableWork, Love Story]
-
A.
Love Story
"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
chosen
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.
Love Story
Love Story is a 1970 romantic drama film best known for its tragic love tale and the famous line "Love means never having to say you're sorry."
-
D.
Sweetheart
"Sweetheart" is a song featured on the album "#1's."
-
E.
Sweetheart
Sweetheart is a 2019 survival horror film in which a young woman stranded on a deserted island must confront a terrifying sea monster.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f646308190b5e277b5f51cd315 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2b4abd08190841c5bb0b0eaa177 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 10, 2026, 5:29 a.m.