Triple
T16264265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trish Van Devere |
E394832
|
entity |
| Predicate | appearedIn |
P795
|
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: [Trish Van Devere, appearedIn, Love Story]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Story Context triple: [Trish Van Devere, appearedIn, Love Story]
-
A.
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."
-
B.
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.
-
C.
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.
-
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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c672248190a4261be4696d52c5 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f8eac988190bdcba6778fbffd64 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:05 a.m.