Triple
T18432853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellflower, California |
E450314
|
entity |
| Predicate | significantLanguageCommunity |
P61052
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Bellflower, California, significantLanguageCommunity, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantLanguageCommunity Context triple: [Bellflower, California, significantLanguageCommunity, Spanish]
-
A.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
B.
demographicsSignificantLanguage
chosen
Indicates that a particular language is significantly represented or prevalent within the demographic profile of a population or group.
-
C.
ethnicLanguageStatus
Indicates the status or role of a language in relation to a particular ethnic group (e.g., primary, secondary, heritage, or minority language).
-
D.
hasNeighboringLanguageCommunity
Indicates that one language community is geographically or socially adjacent to another, allowing for direct contact or interaction between them.
-
E.
shareMajorLanguage
Indicates that the entities have at least one primary or major language in common.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51b183adc8190987bc7749d0e673c |
completed | April 19, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:27 a.m.