Triple
T38490057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mace Mason |
E918029
|
entity |
| Predicate | relationshipToLennyNero |
P204683
|
FINISHED |
| Object | friend |
—
|
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: friend | Statement: [Mace Mason, relationshipToLennyNero, friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLennyNero Context triple: [Mace Mason, relationshipToLennyNero, friend]
-
A.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
B.
relationshipToNedSchneebly
Indicates the specific type of personal, social, or professional relationship an entity has with Ned Schneebly.
-
C.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
-
D.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
-
E.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.