Triple
T16636439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Ross |
E404215
|
entity |
| Predicate | hasNameElementLanguage |
P41819
|
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: [de Ross, hasNameElementLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameElementLanguage Context triple: [de Ross, hasNameElementLanguage, French]
-
A.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
B.
hasFullNameLanguage
chosen
Indicates that the language in which a full name is expressed is associated with that full name.
-
C.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
-
D.
hasNamingLanguageRoot
Indicates that the name of one entity is derived from, or rooted in, the language of another entity.
-
E.
hasLanguageIndependentName
Indicates that an entity possesses a name or label that is the same across all languages, not tied to any specific linguistic form.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378ea4b848190bf7c95dad8a855f0 |
completed | April 18, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.