Triple
T20029229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary Walsh |
E495075
|
entity |
| Predicate | relationshipTypeWithSelinaMeyer |
P132004
|
FINISHED |
| Object | personal aide |
—
|
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: personal aide | Statement: [Gary Walsh, relationshipTypeWithSelinaMeyer, personal aide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithSelinaMeyer Context triple: [Gary Walsh, relationshipTypeWithSelinaMeyer, personal aide]
-
A.
relationshipToSelinaMeyer
chosen
Indicates the specific type of personal or professional relationship an entity has with Selina Meyer.
-
B.
relationshipTypeWithMelanieHealy
Indicates the specific nature or category of relationship that an entity has with Melanie Healy.
-
C.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
D.
relationshipTypeWith Sebastian Wilder
Indicates the specific nature or category of relationship that an entity has with Sebastian Wilder.
-
E.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662908df081909a6c8ccf0dd90fff |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:36 p.m.