Triple
T3211379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Mistakes |
E67287
|
entity |
| Predicate | hasLengthCategory |
P26903
|
FINISHED |
| Object | short song |
—
|
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: short song | Statement: [No Mistakes, hasLengthCategory, short song]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthCategory Context triple: [No Mistakes, hasLengthCategory, short song]
-
A.
hasNameLengthCategory
chosen
Indicates that an entity is associated with a classification describing the length of its name (e.g., short, medium, long).
-
B.
hasCategoryLengthRestriction
Indicates that there is a constraint on the allowable length of a category, such as its name, identifier, or structural size.
-
C.
hasCategoryCount
Indicates the number of distinct categories associated with a given entity.
-
D.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
-
E.
hasNumberCategory
Indicates that an entity is associated with a specific numerical classification or type.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaaba224c8190ad2f4e0ed1c2ca4a |
completed | March 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69ad9e09b83881908801d79c3d9254f9 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.