Triple
T18310490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hui Fei |
E438610
|
entity |
| Predicate | workBasedIn |
P1527
|
FINISHED |
| Object | Republican-era China (setting of Shanghai Express) |
—
|
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: Republican-era China (setting of Shanghai Express) | Statement: [Hui Fei, workBasedIn, Republican-era China (setting of Shanghai Express)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workBasedIn Context triple: [Hui Fei, workBasedIn, Republican-era China (setting of Shanghai Express)]
-
A.
workAt
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
B.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
-
C.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
D.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
E.
workIsPartOf
Indicates that one work is a component, section, or subset of a larger work.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e502180d208190ae7c4f3d0ef3dc55 |
completed | April 19, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.