Triple
T34589002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marjorie Liu |
E888123
|
entity |
| Predicate | hasWrittenNovel |
P78982
|
FINISHED |
| Object | Tiger Eye |
—
|
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: Tiger Eye | Statement: [Marjorie Liu, hasWrittenNovel, Tiger Eye]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWrittenNovel Context triple: [Marjorie Liu, hasWrittenNovel, Tiger Eye]
-
A.
hasWrittenFiction
chosen
Indicates that one entity is the creator or author of fictional written works associated with another entity.
-
B.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
-
C.
hasWrittenAbout
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
D.
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.).
-
E.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
- 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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720cb064c8190bd820ce3e44dc160 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:03 a.m.