Triple
T25508724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stella |
E639313
|
entity |
| Predicate | hasRelationshipTypeWithAstrophil |
P186341
|
FINISHED |
| Object | distant beloved |
—
|
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: distant beloved | Statement: [Stella, hasRelationshipTypeWithAstrophil, distant beloved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithAstrophil Context triple: [Stella, hasRelationshipTypeWithAstrophil, distant beloved]
-
A.
hasRelationshipTypeWithNastasyaFilippovna
Indicates that an entity has a specific type of relationship with Nastasya Filippovna.
-
B.
hasRelationshipTypeWithAngélique
Indicates that one entity has a specific type of relationship or relational status with Angélique.
-
C.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
-
D.
hasRelationshipTypeWithJimmyPorter
Indicates that an entity has a specific type of relationship or connection with Jimmy Porter.
-
E.
hasRelationshipTypeWith Valère
Indicates that an entity stands in a specific, characterized type of relationship with Valère.
- 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_69e75dbd09308190b6b5f0afdc12ec6d |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7cec398ac819081c954a993c323ee |
completed | May 3, 2026, 10:40 p.m. |
Created at: April 21, 2026, 2:48 p.m.