Triple
T14080197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius Tennon |
E338844
|
entity |
| Predicate | producerOf |
P490
|
FINISHED |
| Object | Lila & Eve |
E1056032
|
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: Lila & Eve | Statement: [Julius Tennon, producerOf, Lila & Eve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lila & Eve Context triple: [Julius Tennon, producerOf, Lila & Eve]
-
A.
Lila & Eve
chosen
Lila & Eve is a 2015 crime thriller film starring Viola Davis and Jennifer Lopez as grieving mothers who turn vigilante to seek justice for their murdered children.
-
B.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
C.
Lila
Lila is a novel by Marilynne Robinson that continues her acclaimed Gilead series, exploring themes of grace, poverty, and belonging through the life of its enigmatic title character.
-
D.
Lila
Lila is a character from the Peanuts universe who appears in the animated film "Snoopy, Come Home" as Snoopy’s original owner.
-
E.
Lila
Lila is the daughter of French actress Virginie Ledoyen.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5f759c81909bfd60ab35b0937b |
completed | April 14, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb672c08081908e1ff9030745776a |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.