Triple
T28953428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheng Han |
E731082
|
entity |
| Predicate | ethnicFoundation |
P177322
|
FINISHED |
| Object | Di people |
—
|
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: Di people | Statement: [Cheng Han, ethnicFoundation, Di people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnicFoundation Context triple: [Cheng Han, ethnicFoundation, Di people]
-
A.
ethnicGroupAdvocatedFor
Indicates that one entity actively supported, promoted, or defended the interests or rights of a particular ethnic group.
-
B.
ethnicGroupInFocus
Indicates that a particular ethnic group is the primary subject or focal point within a given context, relation, or description.
-
C.
ethnicGroupHelped
Indicates that one ethnic group provided assistance or support to another entity or group.
-
D.
ethnicGroupTargetedInPolicy
Indicates that a particular ethnic group is the specific focus or target of a given policy, whether for regulation, benefit, restriction, or other differential treatment.
-
E.
ethnicComponents
Indicates that an entity is composed of, associated with, or characterized by one or more specified ethnic groups or ethnic origins.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6fb93224881908fc66fe76115fcdb |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fb17d5ec81909091e37e1ddbe577 |
completed | May 3, 2026, 7:36 a.m. |
Created at: April 28, 2026, 8:45 a.m.