Triple
T14575146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maudie Atkinson |
E342021
|
entity |
| Predicate | relationshipToScout |
P114923
|
FINISHED |
| Object | mentor |
—
|
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: mentor | Statement: [Maudie Atkinson, relationshipToScout, mentor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToScout Context triple: [Maudie Atkinson, relationshipToScout, mentor]
-
A.
relationshipToCreature
Indicates a specified type of relational connection that one entity has toward a particular creature.
-
B.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
C.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
D.
acquaintanceOf
Indicates that one entity knows another in a casual or non-intimate way, without implying close friendship or strong personal ties.
-
E.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f49d58819094fcd2a702e146cb |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:24 a.m.