Triple
T35029401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consider the Lobster and Other Essays |
E1010433
|
entity |
| Predicate | hasEssayTopic |
P73038
|
FINISHED |
| Object | American politics |
—
|
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: American politics | Statement: [Consider the Lobster and Other Essays, hasEssayTopic, American politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEssayTopic Context triple: [Consider the Lobster and Other Essays, hasEssayTopic, American politics]
-
A.
containsEssay
Indicates that one entity includes or holds an essay as part of its contents.
-
B.
containsEssayBy
Indicates that one entity (such as a collection, volume, or publication) includes an essay authored by another specified entity.
-
C.
hasTitleEssay
Indicates that an entity has, is associated with, or is identified by a specific essay title.
-
D.
hasBlogTopic
Indicates that an entity’s blog is associated with or covers a particular topic.
-
E.
notableEssayTopics
chosen
Indicates that the subject is known for having written or addressed the object as a significant or noteworthy essay topic.
- 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7858aa5508190a07dde993b3356fc |
completed | May 3, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.