Triple
T7992930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonah Baldwin |
E186051
|
entity |
| Predicate | relationshipToSamBaldwin |
P80225
|
FINISHED |
| Object | son |
—
|
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: son | Statement: [Jonah Baldwin, relationshipToSamBaldwin, son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSamBaldwin Context triple: [Jonah Baldwin, relationshipToSamBaldwin, son]
-
A.
relationshipToBillyBackus
Indicates the specific familial or social relationship that an entity has to the person named Billy Backus.
-
B.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
C.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
-
D.
relationshipToSalimStoudamire
Indicates the specific type of personal, familial, or professional relationship an entity has with Salim Stoudamire.
-
E.
relationshipToSaintBarbara
Indicates that one entity has a specified relationship or connection to Saint Barbara.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c729afc81909d477b1623ac3f9d |
completed | March 31, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:16 p.m.