Triple
T8827315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montresor |
E210047
|
entity |
| Predicate | settingOfCrime |
P84849
|
FINISHED |
| Object | catacombs beneath his palazzo |
—
|
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: catacombs beneath his palazzo | Statement: [Montresor, settingOfCrime, catacombs beneath his palazzo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfCrime Context triple: [Montresor, settingOfCrime, catacombs beneath his palazzo]
-
A.
settingOfInvestigation
Indicates the context, environment, or circumstances in which an investigation takes place.
-
B.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
positionOnCrime
Indicates a stance, opinion, or policy position that an entity holds regarding crime or crime-related issues.
-
E.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
- F. None of above. chosen
Provenance (4 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc6034e8dc819099116d772e87569a |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cff3608819081d2d7e5c16d44b7 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:47 p.m.