Triple
T3567168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Killicks |
E75476
|
entity |
| Predicate | emotionalRelationshipToJanie |
P46837
|
FINISHED |
| Object | lacks romantic affection for Janie Crawford |
—
|
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: lacks romantic affection for Janie Crawford | Statement: [Logan Killicks, emotionalRelationshipToJanie, lacks romantic affection for Janie Crawford]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalRelationshipToJanie Context triple: [Logan Killicks, emotionalRelationshipToJanie, lacks romantic affection for Janie Crawford]
-
A.
relationshipTypeWithJanieCrawford
Indicates the specific nature or category of relationship that an entity has with Janie Crawford.
-
B.
relationshipToJanieCrawford
chosen
Indicates the specific type of personal or social relationship an entity has with Janie Crawford.
-
C.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
-
D.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
E.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
- F. None of above.
Provenance (3 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0ab51d881908f004fae47ab09d9 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb834779081908468e182d5f6cf02 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.