Triple
T19134646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucifer (Divine Comedy) |
E468404
|
entity |
| Predicate | associatedSin |
P134554
|
FINISHED |
| Object | treachery |
—
|
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: treachery | Statement: [Lucifer (Divine Comedy), associatedSin, treachery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedSin Context triple: [Lucifer (Divine Comedy), associatedSin, treachery]
-
A.
associatedDam
Indicates a relationship where one entity is linked or connected to a specific dam, typically as its related or corresponding dam structure.
-
B.
associatedSingle
Indicates a one-to-one association where an entity is linked to exactly one corresponding related entity.
-
C.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
D.
associated act
Indicates a relationship where one act is connected or linked to another act, typically as a related or accompanying action.
-
E.
associatedFair
Indicates a relationship where one entity is linked or connected to a particular fair, such as being held at, organized by, or otherwise related to that fair.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3ec4c848190af450bf5bf8db5e7 |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:05 p.m.