Triple
T11616860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinatown precinct |
E275530
|
entity |
| Predicate | hasPrimaryCulture |
P44820
|
FINISHED |
| Object | Chinese culture |
—
|
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 culture | Statement: [Chinatown precinct, hasPrimaryCulture, Chinese culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryCulture Context triple: [Chinatown precinct, hasPrimaryCulture, Chinese culture]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
primaryCulture
chosen
Indicates the main or dominant culture associated with an entity, typically in contrast to any secondary or additional cultures.
-
C.
hasPrimaryLanguageSubbranch
Indicates that one language subbranch is the main or principal subbranch associated with a given language or language family.
-
D.
languageOfPrimaryCult
Indicates that a specified language is the main or dominant language used in a particular cult’s primary religious practices or rituals.
-
E.
hasPrimaryLanguageBranch
Indicates that an entity’s main or dominant language belongs to a specified language branch or family.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a04675e08190837a3717242fd0f9 |
completed | April 10, 2026, 7:01 a.m. |
| PD | Predicate disambiguation | batch_69d85dd6503c819081f9045e9d5c4f3f |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.