Triple
T28244011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhaolie Emperor |
E712110
|
entity |
| Predicate | associatedWithPersonalName |
P112539
|
FINISHED |
| Object | Liu Bei |
—
|
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: Liu Bei | Statement: [Zhaolie Emperor, associatedWithPersonalName, Liu Bei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithPersonalName Context triple: [Zhaolie Emperor, associatedWithPersonalName, Liu Bei]
-
A.
associatedName
Indicates that one entity has an alternative or related name that is linked or connected to another entity.
-
B.
usedByPersonalName
Indicates that something (such as an object, resource, or identifier) is used by a person identified by a specific personal name.
-
C.
namedPersonAssociation
chosen
Indicates a relationship where one entity is associated with or identified by a specific personal name.
-
D.
associatedSurname
Indicates that one entity has a surname that is linked or connected to another entity, such as a person, family, or name record.
-
E.
originallyAssociatedWith
Indicates that an entity was first linked, connected, or affiliated with another entity before any later changes in association.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a00d820a7788190a8d54625cd87be68 |
completed | May 10, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_6a00d7c5b40c8190b80413238d04e81e |
completed | May 10, 2026, 7:08 p.m. |
Created at: April 27, 2026, 11 p.m.