Triple
T11020582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaspar Noé |
E260475
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object |
Love
Love is a 2015 French erotic drama film by Gaspar Noé that explores a turbulent, sexually charged relationship through explicit, immersive storytelling.
|
E444830
|
NE FINISHED |
How this triple was built (4 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: [Gaspar Noé, directed, Love]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Context triple: [Gaspar Noé, directed, Love]
-
A.
Love
Love is an American professional basketball player known for his elite rebounding, three-point shooting, and key role in the Cleveland Cavaliers’ 2016 NBA championship.
-
B.
Love
Love is a 2009 cover album by R&B group Boyz II Men featuring their renditions of classic love songs.
-
C.
Love
Love is a complex and multifaceted human emotion characterized by deep affection, attachment, and care for others.
-
D.
Love
"Love" is a soulful pop song by American singer-songwriter Matt Morris, showcasing his emotive vocals and introspective songwriting.
-
E.
Love
Love is a dark, psychologically intense novel by Angela Carter that explores obsession, desire, and self-destruction within a claustrophobic love triangle.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Love Triple: [Gaspar Noé, directed, Love]
Generated description
Love is a 2015 French erotic drama film by Gaspar Noé that explores a turbulent, sexually charged relationship through explicit, immersive storytelling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Love Target entity description: Love is a 2015 French erotic drama film by Gaspar Noé that explores a turbulent, sexually charged relationship through explicit, immersive storytelling.
-
A.
Love
chosen
"Love" is a 2015 erotic drama film directed by Gaspar Noé that explores a turbulent, sexually charged relationship and its emotional aftermath.
-
B.
Love
Love is a dark, psychologically intense novel by Angela Carter that explores obsession, desire, and self-destruction within a claustrophobic love triangle.
-
C.
Love
Love is a Netflix romantic comedy-drama series that explores the complexities of modern relationships through the perspectives of two flawed protagonists.
-
D.
Love
"Love" is a critically acclaimed 1971 Hungarian drama film directed by Károly Makk, renowned for its intimate portrayal of love and resilience under a repressive political regime.
-
E.
Love
"Love" is a 1927 silent romantic drama film directed by Edmund Goulding, best known for starring Greta Garbo and John Gilbert in an adaptation of Leo Tolstoy’s novel "Anna Karenina."
- F. None of above.
Provenance (5 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797baad408190a53fd6941a750f68 |
completed | April 9, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a98725808190903639866a3e745f |
completed | April 18, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69e3abe492388190a2f5752f6bad1220 |
completed | April 18, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b1efe4a88190884eb5186954cf39 |
completed | April 18, 2026, 4:31 p.m. |
Created at: April 8, 2026, 9:25 p.m.