Triple
T37415511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Q. Ross |
E929693
|
entity |
| Predicate | associatedWithEthnicHumor |
P120838
|
FINISHED |
| Object | Jewish-American humor |
—
|
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: Jewish-American humor | Statement: [Leonard Q. Ross, associatedWithEthnicHumor, Jewish-American humor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithEthnicHumor Context triple: [Leonard Q. Ross, associatedWithEthnicHumor, Jewish-American humor]
-
A.
dedicatedToEthnicity
Indicates that something (such as a work, event, or resource) is specifically devoted or addressed to a particular ethnic group.
-
B.
sharesEthnicity
Indicates that two entities belong to the same ethnic group or share the same ethnic background.
-
C.
hasEthnicScope
Indicates that something is relevant or applicable specifically to a particular ethnic group or ethnic context.
-
D.
holderEthnicity
Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
-
E.
hasEthnicTarget
chosen
Indicates that an action, statement, or event is directed toward or targets a specific ethnic group.
- 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.