Triple

T23596029
Position Surface form Disambiguated ID Type / Status
Subject Khalil Kain E582618 entity
Predicate playedCharacter P1507 FINISHED
Object Marvin in Love Jones
Marvin in Love Jones is a supporting character in the 1997 romantic drama film "Love Jones," serving as part of the social circle that shapes the main characters’ relationships and personal journeys.
E1597041 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: Marvin in Love Jones | Statement: [Khalil Kain, playedCharacter, Marvin in Love Jones]
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: Marvin in Love Jones
Triple: [Khalil Kain, playedCharacter, Marvin in Love Jones]
Generated description
Marvin in Love Jones is a supporting character in the 1997 romantic drama film "Love Jones," serving as part of the social circle that shapes the main characters’ relationships and personal journeys.

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_69e248f9e0a08190814772847003b1ff completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b08f9b648190b90d3b2aa49ba85e completed April 29, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f4580d160819087d0b001c554c655 completed May 21, 2026, 5:48 p.m.
NEDg Description generation batch_6a0f4732991c819090acd6744f1b5cd5 completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47edf76c819083722440930ae47c completed May 21, 2026, 5:59 p.m.
Created at: April 17, 2026, 6:42 p.m.