Triple
T5611548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havre de Grace (estate near Wilmington, Delaware) |
E147368
|
entity |
| Predicate | namedLanguage |
P15
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Havre de Grace (estate near Wilmington, Delaware), namedLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedLanguage Context triple: [Havre de Grace (estate near Wilmington, Delaware), namedLanguage, French]
-
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.
recognizedLanguage
Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
-
D.
hasLanguageOfNickname
Indicates that an entity’s nickname is expressed in, or associated with, a particular language.
-
E.
languageDesigned
Indicates that one entity created or developed the language used or associated with 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211fad448190b068b77ed25931d5 |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.