Triple
T37101605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V |
E918716
|
entity |
| Predicate | precedesCareerStageOf |
P110782
|
FINISHED |
| Object | James Valentine’s work with Maroon 5 |
—
|
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: James Valentine’s work with Maroon 5 | Statement: [V, precedesCareerStageOf, James Valentine’s work with Maroon 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedesCareerStageOf Context triple: [V, precedesCareerStageOf, James Valentine’s work with Maroon 5]
-
A.
precedesInCareer
Indicates that one entity’s role, position, or stage in a professional path occurs earlier in time than another entity’s corresponding role, position, or stage in that same career trajectory.
-
B.
chronologicallyPrecedesCareerPhase
chosen
Indicates that one career phase occurs earlier in time than another career phase.
-
C.
hasCareerStage
Indicates the specific phase or stage of a person's or entity's professional or occupational progression.
-
D.
isStageInCareerOf
Indicates that one entity represents a particular phase or stage within the professional career of another entity.
-
E.
hasStageCareer
Indicates that an entity has pursued or been involved in a professional career in stage performance or theater.
- 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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: May 3, 2026, 4:14 p.m.