Triple
T647482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. John’s Cemetery, Worcester, Massachusetts |
E11271
|
entity |
| Predicate | languageOfPlaceName |
P15
|
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: [St. John’s Cemetery, Worcester, Massachusetts, languageOfPlaceName, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPlaceName Context triple: [St. John’s Cemetery, Worcester, Massachusetts, languageOfPlaceName, English]
-
A.
languageName
Indicates the specific name assigned to a language in the relationship.
-
B.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
historicallyDominantLanguageOfAdministrationIn
Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1cb24481909d3b41a56b29dee9 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.