Triple
T2022424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Godzilla (2014 film) |
E44133
|
entity |
| Predicate | hasDarkerToneThan |
P32831
|
FINISHED |
| Object | previous American Godzilla films |
—
|
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: previous American Godzilla films | Statement: [Godzilla (2014 film), hasDarkerToneThan, previous American Godzilla films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDarkerToneThan Context triple: [Godzilla (2014 film), hasDarkerToneThan, previous American Godzilla films]
-
A.
isDarkerThan
chosen
Indicates that one entity has a lower brightness or lightness level than another, making it visually darker in comparison.
-
B.
hasMainContrast
Indicates a primary opposing or differing relationship between two elements, highlighting the main point of contrast between them.
-
C.
hasHeavierSoundThan
Indicates that one entity produces or is associated with a sound that is sonically heavier, more intense, or more forceful than that of another entity.
-
D.
strongerThan
Indicates that one entity possesses greater strength, power, or intensity than another.
-
E.
hasCliffsColor
Indicates that an entity (such as a cliff or cliff area) possesses a specific color attribute.
- F. None of above.
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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8efbe148190901d3650aa60408a |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a389408190a84a54856352f15b |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.