Triple
T24154563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leroy Jenkins |
E598637
|
entity |
| Predicate | hasMemeStatusBy |
P154808
|
FINISHED |
| Object | mid-2000s |
—
|
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: mid-2000s | Statement: [Leroy Jenkins, hasMemeStatusBy, mid-2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemeStatusBy Context triple: [Leroy Jenkins, hasMemeStatusBy, mid-2000s]
-
A.
hasMast
Indicates that an object possesses or is equipped with a mast as part of its structure.
-
B.
hasStatusInMedia
Indicates that an entity is portrayed with a particular status or condition within a specific media work or context.
-
C.
hasStateMuffin
Indicates that an entity is in a particular "muffin" state or condition, typically representing a specific status labeled as "muffin."
-
D.
hasGroupStatus
Indicates that an entity possesses a particular status, role, or condition within a group or collective context.
-
E.
hasRewardStatus
Indicates that an entity possesses a particular reward-related condition, level, or eligibility status within a reward system.
- 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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e4372081909d2b3f7f2af7b407 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 11:31 p.m.