Triple
T13983240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Wedding in Haiti |
E336366
|
entity |
| Predicate | hasSubjectEthnicContext |
P64832
|
FINISHED |
| Object | Haitian |
—
|
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: Haitian | Statement: [A Wedding in Haiti, hasSubjectEthnicContext, Haitian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectEthnicContext Context triple: [A Wedding in Haiti, hasSubjectEthnicContext, Haitian]
-
A.
hasEthnolinguisticContext
chosen
Indicates that something is associated with, shaped by, or understood within a specific ethnolinguistic (cultural and language-based) context.
-
B.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
C.
depictsEthnicContext
Indicates that one entity visually represents or portrays the ethnic background, identity, or cultural context associated with another entity.
-
D.
holderEthnicity
Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
-
E.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character of, another entity.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea2e8808190a1203a6386224bd8 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.