Triple
T13932208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niggamortis |
E335019
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Death Trap |
E1069237
|
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: Death Trap | Statement: [Niggamortis, hasTrack, Death Trap]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Death Trap Context triple: [Niggamortis, hasTrack, Death Trap]
-
A.
Death Trap
chosen
Death Trap is a track from the horrorcore hip-hop album "6 Feet Deep" by the Gravediggaz.
-
B.
Time Trap
Time Trap is a 2017 science fiction adventure film about a group of students who discover a cave where time passes at drastically different speeds.
-
C.
The Trap
"The Trap" is a horror novel by Tabitha King that delves into psychological terror and the darker sides of human relationships in a small-town setting.
-
D.
The Trap
The Trap is a 1966 British adventure drama film set in the Canadian wilderness, starring Rita Tushingham and Oliver Reed.
-
E.
Booby Trap
"Booby Trap" is an episode of Star Trek: The Next Generation in which the crew of the Enterprise-D becomes ensnared in an ancient energy-draining trap while Geordi La Forge works with a holographic recreation of the ship’s designer to find a way out.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1c67e2c8190a14b273af0d93b0a |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:16 p.m.