Triple
T30492937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Devil’s Foot |
E775918
|
entity |
| Predicate | fictionalPoisonName |
P55739
|
FINISHED |
| Object | Devil’s Foot root |
—
|
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: Devil’s Foot root | Statement: [The Adventure of the Devil’s Foot, fictionalPoisonName, Devil’s Foot root]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalPoisonName Context triple: [The Adventure of the Devil’s Foot, fictionalPoisonName, Devil’s Foot root]
-
A.
poisonUsed
Indicates that one entity employed poison as a means to harm, kill, or incapacitate another entity.
-
B.
fictionalKillerName
Indicates that an entity is known by a particular fictional name as a killer or murderer.
-
C.
hasFictionalSubstance
chosen
Indicates that one entity includes, contains, or involves a fictional or imaginary substance as part of its composition, setting, or narrative.
-
D.
fictionalDisease
Indicates that an entity is associated with, afflicted by, or otherwise characterized by a disease that is imaginary or does not exist in reality.
-
E.
fictionalSpellName
Indicates that an entity is associated with, uses, or is identified by a particular fictional spell name.
- 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_69f22498c5d481908aaea89e6fab8280 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: April 29, 2026, 8:14 p.m.