Triple
T31460352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Nham |
E802573
|
entity |
| Predicate | hasSubjectOfWriting |
P14097
|
FINISHED |
| Object | DeepMind |
—
|
NE NERFINISHED |
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: DeepMind | Statement: [John Nham, hasSubjectOfWriting, DeepMind]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectOfWriting Context triple: [John Nham, hasSubjectOfWriting, DeepMind]
-
A.
hasWrittenAbout
chosen
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
B.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
-
C.
hasWrittenWorkType
Indicates that an entity (typically a written work) is associated with a specific type or category of written work (such as novel, article, report, etc.).
-
D.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
E.
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.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: April 30, 2026, 9:19 p.m.