Triple
T17776839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine Grove Cemetery (Manchester, New Hampshire) |
E443791
|
entity |
| Predicate | hasLanguageOfLocalContext |
P91957
|
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: [Pine Grove Cemetery (Manchester, New Hampshire), hasLanguageOfLocalContext, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfLocalContext Context triple: [Pine Grove Cemetery (Manchester, New Hampshire), hasLanguageOfLocalContext, English]
-
A.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
-
C.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
D.
hasPrimaryLanguageNearby
chosen
Indicates that an entity is associated with a primary language that is predominantly used or present in its immediate geographic or contextual vicinity.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4871d43a481908aacde69bd8091b0 |
completed | April 19, 2026, 7:41 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.