Triple
T11616873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinatown precinct |
E275530
|
entity |
| Predicate | hasCommonInstitutionType |
P29027
|
FINISHED |
| Object | Chinese temples |
—
|
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 temples | Statement: [Chinatown precinct, hasCommonInstitutionType, Chinese temples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonInstitutionType Context triple: [Chinatown precinct, hasCommonInstitutionType, Chinese temples]
-
A.
commonInstitution
Indicates that two or more entities share affiliation with the same institution (such as an organization, school, or company).
-
B.
associatedInstitutionType
chosen
Indicates the type or category of institution with which an entity is associated.
-
C.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
D.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
E.
hasPrimaryInstitutionType
Indicates that an entity’s main or principal institutional classification or category is of a specified type.
- 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.