Triple
T30492953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Devil’s Foot |
E775918
|
entity |
| Predicate | hasDeductionType |
P171173
|
FINISHED |
| Object | forensic reasoning about toxic fumes |
—
|
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: forensic reasoning about toxic fumes | Statement: [The Adventure of the Devil’s Foot, hasDeductionType, forensic reasoning about toxic fumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeductionType Context triple: [The Adventure of the Devil’s Foot, hasDeductionType, forensic reasoning about toxic fumes]
-
A.
deductionType
chosen
Indicates the specific kind or category of deduction that applies within a given context or system.
-
B.
deductsFrom
Indicates that a specified amount, value, or resource is subtracted from another entity, reducing the latter accordingly.
-
C.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
D.
taxDeductible
Indicates that an expense, contribution, or item is eligible to be subtracted from taxable income under applicable tax rules.
-
E.
typeOfTaxCredit
Indicates that one entity is a specific kind or category of tax credit in relation to another entity.
- 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_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: April 29, 2026, 8:14 p.m.