Triple
T30958154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fortescues of Fallapit |
E788732
|
entity |
| Predicate | languageOfFamilyRecords |
P8532
|
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: [Fortescues of Fallapit, languageOfFamilyRecords, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFamilyRecords Context triple: [Fortescues of Fallapit, languageOfFamilyRecords, English]
-
A.
languageOfFamily
chosen
Indicates the language or languages commonly used or associated with a particular family.
-
B.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
-
C.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
D.
languageFamilyOf
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
-
E.
peopleNameLanguageFamily
Indicates that a person’s name belongs to or is derived from a particular language family.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff5803c02c81908b63067119f5e684 |
completed | May 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69ff576d8b308190b49a1e072a0ae661 |
completed | May 9, 2026, 3:49 p.m. |
Created at: April 29, 2026, 8:54 p.m.