Triple
T6529870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | It’s a Wrap |
E152202
|
entity |
| Predicate | hasTikTokResurgence |
P70527
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [It’s a Wrap, hasTikTokResurgence, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTikTokResurgence Context triple: [It’s a Wrap, hasTikTokResurgence, yes]
-
A.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
B.
isPopularOnSocialMedia
Indicates that an entity is widely followed, frequently engaged with, or broadly recognized across social media platforms.
-
C.
socialPhenomenon
Indicates a relationship where an event, behavior, or pattern emerges from and affects interactions within a society or group.
-
D.
hasOnlineTrendType
chosen
Indicates that an entity is associated with a specific category or type of online trend.
-
E.
wentViralOn
Indicates that content rapidly spread and gained widespread attention or popularity on a particular platform or medium.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adac53b0819097fece48a75cc48f |
completed | March 27, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.