Triple
T3821494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galatasaray High School |
E84382
|
entity |
| Predicate | otherNameLanguage |
P12203
|
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: [Galatasaray High School, otherNameLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherNameLanguage Context triple: [Galatasaray High School, otherNameLanguage, French]
-
A.
originalNameLanguage
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
B.
otherLanguage
chosen
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
C.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
D.
nameInOriginalLanguage
Indicates that an entity’s name is given in its original or native language form.
-
E.
languageCommonlyCalled
Indicates that one language is commonly referred to or known by a particular alternative name or label.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.