Triple
T26206867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Money for Nothing |
E655378
|
entity |
| Predicate | containsIntertext |
P52226
|
FINISHED |
| Object | I want my MTV |
—
|
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: I want my MTV | Statement: [Money for Nothing, containsIntertext, I want my MTV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsIntertext Context triple: [Money for Nothing, containsIntertext, I want my MTV]
-
A.
hasIntercalation
Indicates that an entity includes or undergoes the insertion of additional elements (such as units, segments, or periods) into an existing ordered sequence or structure.
-
B.
intertextualRelation
chosen
Indicates a relationship in which one text references, echoes, or otherwise meaningfully connects to another text.
-
C.
includesParatext
Indicates that one entity contains or is accompanied by paratextual material (such as prefaces, notes, or other supplementary text) related to another entity.
-
D.
containsIntertitlesFrom
Indicates that one entity includes or incorporates intertitles that originate from another entity.
-
E.
containsInterpretationOf
Indicates that one entity includes or embodies an interpretation or understanding of another entity.
- 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_69ee5b49adb4819086545280d4ef6337 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 26, 2026, 8:51 p.m.