Triple
T31435460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masjid Al-Bukhari, Wellingborough |
E801912
|
entity |
| Predicate | languageOfCommunityUse |
P115774
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Masjid Al-Bukhari, Wellingborough, languageOfCommunityUse, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCommunityUse Context triple: [Masjid Al-Bukhari, Wellingborough, languageOfCommunityUse, English]
-
A.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
B.
laterLanguageOfCommunity
Indicates that one language developed later in time as the language used by a particular community, succeeding an earlier community language.
-
C.
languageUsedInLocality
chosen
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
D.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
E.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
- 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff7eb7189c81909a8f73fbc4c48e02 |
completed | May 9, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69ff7e54e11081908fb5ce10c5aa7b53 |
completed | May 9, 2026, 6:35 p.m. |
Created at: April 30, 2026, 9:01 p.m.