Triple
T15500792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orin Incandenza |
E378945
|
entity |
| Predicate | relationshipToAvernaIncandenza |
P118896
|
FINISHED |
| Object | troubled |
—
|
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: troubled | Statement: [Orin Incandenza, relationshipToAvernaIncandenza, troubled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAvernaIncandenza Context triple: [Orin Incandenza, relationshipToAvernaIncandenza, troubled]
-
A.
relationshipToVeronika
Indicates the specific type of personal, social, or familial relationship that one entity has to Veronika.
-
B.
relationshipWithAngelEyes
Indicates a personal or significant connection that an entity has with the individual referred to as AngelEyes.
-
C.
relationshipToTopa
Indicates a familial or social relationship that an entity has specifically with Topa.
-
D.
relationshipToCandide
Indicates the specific type of relationship or connection an entity has to the entity named Candide.
-
E.
relationshipToPetra
Indicates the specific type of relationship or connection that one entity has to Petra.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcb4e8c81908e4ab463e3ae252b |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:54 a.m.