Triple
T31538115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Guangbi |
E804664
|
entity |
| Predicate | roleInAnLushanRebellion |
P88009
|
FINISHED |
| Object | commanded loyalist forces |
—
|
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: commanded loyalist forces | Statement: [Li Guangbi, roleInAnLushanRebellion, commanded loyalist forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInAnLushanRebellion Context triple: [Li Guangbi, roleInAnLushanRebellion, commanded loyalist forces]
-
A.
roleInRevolt
chosen
Indicates the specific function, position, or level of participation an entity had within a particular revolt or uprising.
-
B.
roleDuringSecondSinoJapaneseWar
Indicates the specific role, position, or function an entity held or performed during the Second Sino-Japanese War.
-
C.
actsOfRebellion
Indicates actions that deliberately oppose, resist, or defy an established authority, rule, or controlling force.
-
D.
roleInMutiny
Indicates that one entity participated in a mutiny with a specific role or capacity in that rebellious action.
-
E.
roleInRomanceOfTheThreeKingdoms
Indicates the narrative role or function an entity plays within the story of *Romance of the Three Kingdoms*.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffbf84f4948190b41a7bba07ae61ec |
completed | May 9, 2026, 11:13 p.m. |
| PD | Predicate disambiguation | batch_69ffbf0a59f88190870dbe25d8a63a00 |
completed | May 9, 2026, 11:11 p.m. |
Created at: April 30, 2026, 10:04 p.m.