Triple
T3847533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nini |
E85207
|
entity |
| Predicate | representsHost |
P51903
|
FINISHED |
| Object | Beijing as host city of 2008 Olympics |
—
|
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: Beijing as host city of 2008 Olympics | Statement: [Nini, representsHost, Beijing as host city of 2008 Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsHost Context triple: [Nini, representsHost, Beijing as host city of 2008 Olympics]
-
A.
representedTo
Indicates that one entity formally acted on behalf of or served as the representative of another entity in a given context or interaction.
-
B.
representsMember
Indicates that one entity is a member or constituent part of another entity, such as an individual belonging to a group or organization.
-
C.
memberRepresents
Indicates that one entity serves as an official representative or delegate acting on behalf of another entity within a group, organization, or body.
-
D.
host
Indicates that one entity provides space, resources, or services to accommodate, receive, or entertain another entity.
-
E.
alsoHosted
Indicates that the subject entity, in addition to others, served as a host for the same event or activity.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcb069881909d3536b18b7802a7 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:18 p.m.