Triple
T4663075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Heard |
E102779
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Zombieland |
E142421
|
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: Zombieland | Statement: [Amber Heard, notableWork, Zombieland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zombieland Context triple: [Amber Heard, notableWork, Zombieland]
-
A.
Zombieland
chosen
Zombieland is a 2009 horror-comedy film about a group of survivors navigating a zombie apocalypse with a mix of humor, gore, and quirky survival rules.
-
B.
Zombies
Zombies is a popular cooperative survival-horror game mode featuring waves of undead enemies, best known from its inclusion in Treyarch’s Call of Duty titles.
-
C.
Zombie
A Zombie in Minecraft is a common hostile undead mob that attacks players and villagers, often spawning in dark areas and burning in sunlight.
-
D.
Zombie
"Zombie" is a dark psychological horror novel by Joyce Carol Oates that explores the mind of a serial killer inspired by real-life murderer Jeffrey Dahmer.
-
E.
World War Z
World War Z is a 2013 apocalyptic action-horror film starring Brad Pitt that depicts a global zombie pandemic and humanity’s desperate efforts to survive.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632d6150819085bab97021c0235a |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfafcd3908190aabf7975017ce337 |
completed | March 21, 2026, 1:57 a.m. |
Created at: March 20, 2026, 1:15 p.m.