Triple
T35548404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil or Angel |
E1027282
|
entity |
| Predicate | hasLaterPopularityAs |
P156060
|
FINISHED |
| Object | pop hit |
—
|
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: pop hit | Statement: [Devil or Angel, hasLaterPopularityAs, pop hit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaterPopularityAs Context triple: [Devil or Angel, hasLaterPopularityAs, pop hit]
-
A.
achievedPopularityIn
Indicates that an entity became popular or widely recognized within a specified place, group, or context.
-
B.
subsequentlyPopularIn
chosen
Indicates that something became popular in a particular place, group, or context after an initial point in time or after another event.
-
C.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
D.
achievedPopularityVia
Indicates that an entity gained recognition or widespread acceptance through a particular method, channel, or means.
-
E.
wasPopularBefore
Indicates that one entity enjoyed a higher level of popularity than another during an earlier time period.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.