Triple
T31520575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gutrune |
E804194
|
entity |
| Predicate | relationshipToSiegfried |
P207448
|
FINISHED |
| Object | wife |
—
|
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: wife | Statement: [Gutrune, relationshipToSiegfried, wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSiegfried Context triple: [Gutrune, relationshipToSiegfried, wife]
-
A.
hasRelationshipTypeWithSieglinde
Indicates that an entity has a specific type of relationship or connection with Sieglinde.
-
B.
relationshipTypeWith Túrin Turambar
Indicates the specific kind of relationship or connection that an entity has with Túrin Turambar.
-
C.
relationshipToManfred
Indicates the specific type of relationship or connection that one entity has to the individual named Manfred.
-
D.
relationToShannara
Indicates a relationship or connection that an entity has to the Shannara universe, works, or related elements.
-
E.
relationshipTypeWithWilhelm Meister
Indicates the specific type or nature of the relationship that an entity has with Wilhelm Meister.
- 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_69f348cf839c81908657048402f7f97b |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 9:55 p.m.