Triple
T38370730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playing Around Before the Party Starts |
E892570
|
entity |
| Predicate | visualCompanionTo |
P69911
|
FINISHED |
| Object | Because the Internet |
—
|
NE NERFINISHED |
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: Because the Internet | Statement: [Playing Around Before the Party Starts, visualCompanionTo, Because the Internet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualCompanionTo Context triple: [Playing Around Before the Party Starts, visualCompanionTo, Because the Internet]
-
A.
visualCompanion
chosen
Indicates that one entity serves as a visual counterpart, partner, or accompanying element to another in a visual context.
-
B.
viewsCompanions
Indicates that an entity observes or looks at its companions or associates.
-
C.
visualCenterpiece
Indicates that one entity serves as the primary visual focus or dominant visual element in relation to another entity.
-
D.
viewOnCompanions
Indicates a relationship where one entity holds a particular opinion, perspective, or attitude about its companions or associated entities.
-
E.
visualExperience
Indicates a relationship where an entity undergoes or has a particular experience involving visual perception or seeing.
- 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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.