Triple
T11760207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac and Me |
E279633
|
entity |
| Predicate | hasCultReputationAs |
P15525
|
FINISHED |
| Object | one of the worst films ever made |
—
|
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: one of the worst films ever made | Statement: [Mac and Me, hasCultReputationAs, one of the worst films ever made]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCultReputationAs Context triple: [Mac and Me, hasCultReputationAs, one of the worst films ever made]
-
A.
hasCultSince
Indicates that an entity has had an organized group of devoted followers (a cult) continuously since a specified time or date.
-
B.
hasCultFollowing
chosen
Indicates that something has attracted a small but highly dedicated and enthusiastic group of supporters or fans.
-
C.
hasReputationAmong
Indicates that an entity is regarded or perceived in a particular way by a specified group or audience.
-
D.
hasCulticPractice
Indicates that an entity engages in, observes, or is associated with a specific religious or ritualistic practice.
-
E.
hasMysteryCult
Indicates that an entity is associated with, participates in, or possesses a mystery cult, typically involving secret or esoteric religious practices.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.