Triple
T2142031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Case of You |
E46778
|
entity |
| Predicate | hasKeyLine |
P36573
|
FINISHED |
| Object | "I could drink a case of you and I would still be on my feet" |
—
|
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: "I could drink a case of you and I would still be on my feet" | Statement: [A Case of You, hasKeyLine, "I could drink a case of you and I would still be on my feet"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyLine Context triple: [A Case of You, hasKeyLine, "I could drink a case of you and I would still be on my feet"]
-
A.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
-
B.
hasLineGroup
Indicates that one entity is associated with, or belongs to, a particular group or collection of lines.
-
C.
containsLine
Indicates that one entity includes or encloses a specific line within its spatial or structural extent.
-
D.
hasLineElementForm
Indicates that something takes the form or representation of a line element within a given structure or context.
-
E.
hasKeyElement
Indicates that one entity contains or depends on another entity that serves as a primary or essential component.
- F. None of above. chosen
Provenance (4 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbea8bd4881908f72019a5acf6174 |
completed | March 7, 2026, 5:59 a.m. |
Created at: March 4, 2026, 7:44 p.m.