Triple
T34981174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. White |
E1008817
|
entity |
| Predicate | guidesCareerOf |
P90207
|
FINISHED |
| Object | The Wonders |
—
|
NE NERFINISHED |
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: The Wonders | Statement: [Mr. White, guidesCareerOf, The Wonders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guidesCareerOf Context triple: [Mr. White, guidesCareerOf, The Wonders]
-
A.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
-
B.
helpsLaunchCareerOf
chosen
Indicates that one entity plays a significant role in starting, advancing, or establishing the professional career of another entity.
-
C.
careerTackles
Indicates the total number of tackles a player has made over the course of their entire career.
-
D.
careerAssists
Indicates the total number of assists a player has recorded over the entire span of their professional or competitive career.
-
E.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
- 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.