Triple
T8076115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shot Orange Marilyn |
E188494
|
entity |
| Predicate | hasSeriesMemberType |
P121
|
FINISHED |
| Object | Shot Marilyns color variant |
—
|
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: Shot Marilyns color variant | Statement: [Shot Orange Marilyn, hasSeriesMemberType, Shot Marilyns color variant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeriesMemberType Context triple: [Shot Orange Marilyn, hasSeriesMemberType, Shot Marilyns color variant]
-
A.
hasMemberType
chosen
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
B.
hasStandardSeries
Indicates that an entity is associated with, or belongs to, a designated standard series or standardized sequence.
-
C.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
-
D.
hasAlternateMemberType
Indicates that an entity is associated with a different or substitute type of member than its primary or standard member type.
-
E.
hasVariantSeries
Indicates a relationship where one entity is a variant or alternative series derived from or associated with another series.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb404dc7ac8190956b5c2f5aeac6b2 |
completed | March 31, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:28 p.m.