Triple
T38027829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Koch |
E948827
|
entity |
| Predicate | wrote about |
P14097
|
FINISHED |
| Object | love |
—
|
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: love | Statement: [Kenneth Koch, wrote about, love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wrote about Context triple: [Kenneth Koch, wrote about, love]
-
A.
hasWrittenAbout
chosen
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
B.
wrote
Indicates that an entity is the author or creator of a written work involving another entity.
-
C.
wroteIn
Indicates that an entity authored or composed something using a particular language, medium, or writing system.
-
D.
writtenAgainst
Indicates that a written work (such as a document, article, or statement) is composed in opposition to, or as a critique or complaint about, a particular target.
-
E.
writtenIn
Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc99760d48190a5d0d00c36307456 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.