Triple
T22100554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phenomena |
E546157
|
entity |
| Predicate | alternateTitle |
P39
|
FINISHED |
| Object | Creepers |
—
|
NE NERFINISHED |
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: Creepers | Statement: [Phenomena, alternateTitle, Creepers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Creepers Context triple: [Phenomena, alternateTitle, Creepers]
-
A.
Creepers
chosen
Creepers is a 2005 thriller novel by David Morrell that follows a group of urban explorers whose night inside an abandoned hotel turns into a deadly struggle for survival.
-
B.
Creeper
Creeper is an iconic hostile mob from the game Minecraft known for silently approaching players and exploding.
-
C.
Creeper
Creeper is the Horned King's bumbling, goblin-like henchman from Disney's animated dark fantasy film "The Black Cauldron."
-
D.
The Creeper
The Creeper is a DC Comics antihero known for his garish yellow-and-green costume, maniacal laughter, and transformation from TV host Jack Ryder into a bizarre, acrobatic crimefighter.
-
E.
The Creep
The Creep is a film featuring actor Tom Mison, likely a lesser-known project in his body of work.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291501508190ad5689be5abb2ba6 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.