Triple
T3494057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille (1921 film) – costume and set design |
E73804
|
entity |
| Predicate | typeOfSets |
P48728
|
FINISHED |
| Object | studio-built interior sets |
—
|
LITERAL 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: studio-built interior sets | Statement: [Camille (1921 film) – costume and set design, typeOfSets, studio-built interior sets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSets Context triple: [Camille (1921 film) – costume and set design, typeOfSets, studio-built interior sets]
-
A.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
B.
typeOfEnsemble
Indicates the specific kind or category of ensemble that an entity belongs to or represents.
-
C.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
D.
typeOfSettlement
Indicates the specific category or classification of a settlement (e.g., city, town, village) that characterizes what kind of settlement it is.
-
E.
set
Indicates that an entity places, positions, or establishes another entity into a particular state, configuration, or location.
- F. None of above. chosen
Provenance (4 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbaebed881909d9cbc9c4c1f138f |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb055ed2481908171effe28151cf9 |
completed | March 8, 2026, 5:22 p.m. |
Created at: March 8, 2026, 3:18 p.m.