Triple
T11434191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raphaël Colantonio |
E270961
|
entity |
| Predicate | designed |
P184
|
FINISHED |
| Object | Dishonored |
E266332
|
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: Dishonored | Statement: [Raphaël Colantonio, designed, Dishonored]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dishonored Context triple: [Raphaël Colantonio, designed, Dishonored]
-
A.
Dishonored
chosen
Dishonored is a stealth-action video game set in a dark, steampunk-inspired world where players use supernatural abilities and gadgets to navigate branching, choice-driven missions.
-
B.
Dishonored
Dishonored is a 1931 pre-Code espionage drama film directed by Josef von Sternberg and starring Marlene Dietrich as a World War I spy.
-
C.
Vampyr
Vampyr is a 1932 German-French horror film by Carl Theodor Dreyer, renowned for its dreamlike, atmospheric take on vampire folklore.
-
D.
We Happy Few
We Happy Few is a dystopian action-adventure game set in an alternate 1960s England where citizens are forced to take a mind-altering drug to maintain a facade of happiness.
-
E.
Brimstone
Brimstone is a 2016 dark Western thriller film in which Dakota Fanning plays a mute frontier woman pursued by a vengeful preacher.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c485f481909dd3d9b0993f3faf |
completed | April 9, 2026, 8:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739644ed48190896d7b2b6c3b5f8f |
completed | May 3, 2026, 12:02 p.m. |
Created at: April 8, 2026, 9:35 p.m.