Triple
T24111744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Baxter |
E597394
|
entity |
| Predicate | relationshipTypeWith Godwin Baxter |
P155100
|
FINISHED |
| Object | creator and guardian |
—
|
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: creator and guardian | Statement: [Bella Baxter, relationshipTypeWith Godwin Baxter, creator and guardian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Godwin Baxter Context triple: [Bella Baxter, relationshipTypeWith Godwin Baxter, creator and guardian]
-
A.
relationshipTypeWith Eugene Gant
Indicates the specific nature or category of relationship that an entity has with Eugene Gant.
-
B.
relationshipTypeWith W. O. Gant
Indicates the specific nature or category of relational connection that an entity has with W. O. Gant.
-
C.
relationshipTypeWithHudBannon
Indicates the specific nature or category of relationship that an entity has with the person or entity named Hud Bannon.
-
D.
historicalRelationship
Indicates a relationship that existed between entities in the past, often tied to a specific historical period, context, or event.
-
E.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
- 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_69e288c60f9c8190af948d7354aedbeb |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1de1bd81c8190a44f07487d2ba176 |
completed | April 29, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17b58012c81909106b332db399023 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 11:03 p.m.