Triple
T18982934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester station |
E464475
|
entity |
| Predicate | hasLanguageCommunityNearby |
P4647
|
FINISHED |
| Object | Greek community |
—
|
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: Greek community | Statement: [Chester station, hasLanguageCommunityNearby, Greek community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageCommunityNearby Context triple: [Chester station, hasLanguageCommunityNearby, Greek community]
-
A.
hasNeighboringLanguageCommunity
Indicates that one language community is geographically or socially adjacent to another, allowing for direct contact or interaction between them.
-
B.
hasPrimaryLanguageNearby
Indicates that an entity is associated with a primary language that is predominantly used or present in its immediate geographic or contextual vicinity.
-
C.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
D.
hasSecondaryLanguageNearby
Indicates that an entity has at least one secondary language present or used in its immediate vicinity or surrounding context.
-
E.
hasNearbyCommunity
chosen
Indicates that one entity has another community located close to it in geographic or spatial terms.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65de6288190a53a3fdd59013d2d |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.