Triple
T27157722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifehacker |
E682565
|
entity |
| Predicate | typicalArticleLength |
P18065
|
FINISHED |
| Object | short-form |
—
|
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-form | Statement: [Lifehacker, typicalArticleLength, short-form]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalArticleLength Context triple: [Lifehacker, typicalArticleLength, short-form]
-
A.
articleLength
Indicates the length or size of an article, typically measured in units such as words, characters, or pages.
-
B.
typicalArticle
Indicates that one entity is a standard, representative, or commonly occurring instance of the type or category denoted by the other entity.
-
C.
articleLengthPolicy
Indicates that there is a rule or constraint governing the acceptable length of an article.
-
D.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
E.
articleCountApprox
Indicates that the relationship specifies an approximate number of articles associated with an 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ff90b673248190b4dda9e005642d17 |
completed | May 9, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69ff8d5bee1081909274052945e98a6f |
completed | May 9, 2026, 7:39 p.m. |
Created at: April 27, 2026, 9:17 a.m.