Triple
T3282362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tripmaster Monkey: His Fake Book |
E68900
|
entity |
| Predicate | mainCharacterEthnicity |
P28254
|
FINISHED |
| Object | Chinese American |
—
|
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: Chinese American | Statement: [Tripmaster Monkey: His Fake Book, mainCharacterEthnicity, Chinese American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterEthnicity Context triple: [Tripmaster Monkey: His Fake Book, mainCharacterEthnicity, Chinese American]
-
A.
protagonistEthnicity
chosen
Indicates the ethnic background or cultural heritage associated with a work’s main character.
-
B.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
C.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
D.
protagonistNationality
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
E.
mainCharacterAffiliation
Indicates the group, organization, or side with which the main character is formally or primarily aligned.
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0345d448190a1f936abe7748e33 |
completed | March 8, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_69ada421fadc8190b7c7d3c8afd20061 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.