Triple
T19584066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Headlight |
E490065
|
entity |
| Predicate | hasEnduringRadioPopularity |
P57498
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [One Headlight, hasEnduringRadioPopularity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnduringRadioPopularity Context triple: [One Headlight, hasEnduringRadioPopularity, true]
-
A.
hasEnduringPopularityOn
chosen
Indicates that something continues to be widely liked, used, or appreciated on a particular platform, medium, or context over an extended period of time.
-
B.
hasEnduringPopCulturePresence
Indicates that the subject continues to appear in, influence, or be referenced within popular culture over an extended period of time.
-
C.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
D.
hasPopularityCharacteristic
Indicates that an entity possesses a particular attribute or quality related to its level or type of popularity.
-
E.
contributedToPopularityInDecade
Indicates that something played a role in increasing the popularity of another thing during a specific decade.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e64050127c8190b93b8716a1a4ad81 |
completed | April 20, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:42 p.m.