Triple
T34539787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shi Chaoyi |
E886773
|
entity |
| Predicate | enemyGeneral |
P1698
|
FINISHED |
| Object | Li Guangbi |
—
|
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: Li Guangbi | Statement: [Shi Chaoyi, enemyGeneral, Li Guangbi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enemyGeneral Context triple: [Shi Chaoyi, enemyGeneral, Li Guangbi]
-
A.
enemyCharacter
Indicates that one character is hostile or opposed to another, typically treating them as an adversary or foe.
-
B.
enemyType
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
C.
primaryEnemy
Indicates that one entity is the main or most significant adversary or opponent of another entity.
-
D.
opposingCommander
chosen
Indicates that one entity serves as the commanding officer of a force that is in opposition or conflict with the force commanded by another entity.
-
E.
enemyOrganization
Indicates that one organization is considered an adversary or opponent of another organization, typically in a hostile or competitive context.
- 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71ff1a86481908210dffd1bd27001 |
completed | May 3, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.