Triple
T29694797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Lane |
E751317
|
entity |
| Predicate | columnTopic |
P165591
|
FINISHED |
| Object | cooking |
—
|
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: cooking | Statement: [Elizabeth Lane, columnTopic, cooking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: columnTopic Context triple: [Elizabeth Lane, columnTopic, cooking]
-
A.
column
Indicates a vertical structural element that supports or separates parts within a larger construction or arrangement.
-
B.
topicOfDiscourse
chosen
Indicates that something serves as the subject or focus of a particular discussion, conversation, or communicative act.
-
C.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
subjectCategories
Indicates that an entity is associated with one or more subject-based categories or classifications.
- 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_69f0d6266f8481909e70bb41cda18587 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672af46e48190b76e9298e7d23eef |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:19 p.m.