Triple
T15452350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trustfall |
E371682
|
entity |
| Predicate | theme |
P261
|
FINISHED |
| Object | Love |
E591302
|
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 | Statement: [Trustfall, theme, Love]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Context triple: [Trustfall, theme, Love]
-
A.
Love
"Love" is an essay by Ralph Waldo Emerson that explores the nature, spiritual significance, and transformative power of romantic affection and human connection.
-
B.
Love
"Love" is a 2015 erotic drama film directed by Gaspar Noé that explores a turbulent, sexually charged relationship and its emotional aftermath.
-
C.
Love
chosen
Love is a complex and multifaceted human emotion characterized by deep affection, attachment, and care for others.
-
D.
Love
"Love" is a photomontage artwork by German Dada artist Hannah Höch, reflecting her innovative collage techniques and critical engagement with gender and social norms.
-
E.
Love
Love is a 2003 novel by Toni Morrison that explores the intertwined lives of several women connected by their relationships to a charismatic, deceased hotel owner.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03efaf82c81908b464e37ce9c159a |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b3c5a481908057e94fd84f3cfc |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:30 a.m.