Triple
T1574551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Library Company of Philadelphia |
E33617
|
entity |
| Predicate | originalLanguageOfName |
P28203
|
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: [Library Company of Philadelphia, originalLanguageOfName, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageOfName Context triple: [Library Company of Philadelphia, originalLanguageOfName, English]
-
A.
originalNameLanguage
chosen
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
B.
nameInOriginalLanguage
Indicates that an entity’s name is given in its original or native language form.
-
C.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
D.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
-
E.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907ba63c88190b60c14dec8d1e40f |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.