Triple
T957348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Frost |
E20652
|
entity |
| Predicate | readPoemAt |
P21836
|
FINISHED |
| Object | inauguration of John F. Kennedy |
—
|
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: inauguration of John F. Kennedy | Statement: [Robert Frost, readPoemAt, inauguration of John F. Kennedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readPoemAt Context triple: [Robert Frost, readPoemAt, inauguration of John F. Kennedy]
-
A.
containsPoem
Indicates that one entity includes or holds a poem as part of its contents.
-
B.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
C.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
-
D.
poet
Indicates that an entity creates poetry or is recognized for engaging in the activity of writing poems.
-
E.
readingExperience
Indicates the relationship in which an entity engages with written or visual material, capturing the act, manner, or quality of that reading activity.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fac2bc8190a66feb70c68899b2 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.