Triple
T11678510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia (1977 film) |
E277553
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Julia (character)
Julia is the courageous, politically engaged title character of the 1977 film "Julia," who risks her life resisting fascism in pre–World War II Europe.
|
E940496
|
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: Julia (character) | Statement: [Julia (1977 film), character, Julia (character)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julia (character) Context triple: [Julia (1977 film), character, Julia (character)]
-
A.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
B.
Júlia
Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
-
C.
Julia (TV series)
Julia is an American television drama series inspired by the life and career of pioneering TV chef Julia Child, exploring her impact on cooking, media, and culture in the 1960s.
-
D.
Juliaetta
Juliaetta is a small rural city in north-central Idaho, known for its agricultural surroundings and location in the Clearwater River region.
-
E.
Jula
Jula is a major Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
- 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: Julia (character) Triple: [Julia (1977 film), character, Julia (character)]
Generated description
Julia is the courageous, politically engaged title character of the 1977 film "Julia," who risks her life resisting fascism in pre–World War II Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Julia (character) Target entity description: Julia is the courageous, politically engaged title character of the 1977 film "Julia," who risks her life resisting fascism in pre–World War II Europe.
-
A.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
B.
Júlia
Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
-
C.
Julia (TV series)
Julia is an American television drama series inspired by the life and career of pioneering TV chef Julia Child, exploring her impact on cooking, media, and culture in the 1960s.
-
D.
Juliaetta
Juliaetta is a small rural city in north-central Idaho, known for its agricultural surroundings and location in the Clearwater River region.
-
E.
Jula
Jula is a major Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
- F. None of above. chosen
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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a46000a48190888ad1a6ade052e3 |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef14007dd08190b60640be9949ca26 |
completed | April 27, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69ef35527f908190b681afdae3aec319 |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef51ec07ec8190b5cd97cf909388f0 |
completed | April 27, 2026, 12:09 p.m. |
Created at: April 8, 2026, 9:40 p.m.