Triple
T24608794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City derby |
E609058
|
entity |
| Predicate | hasDerbyNameLanguage |
P40387
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Mexico City derby, hasDerbyNameLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDerbyNameLanguage Context triple: [Mexico City derby, hasDerbyNameLanguage, Spanish]
-
A.
hasDerbyName
Indicates that an entity is known by or uses a specific derby name, typically as an alternate or performance-related identity.
-
B.
hasLanguageOfNickname
chosen
Indicates that an entity’s nickname is expressed in, or associated with, a particular language.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
E.
hasOfficialLanguageNameInGerman
Indicates that an entity has an official language name expressed specifically in the German language.
- 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_69e2c4d060e08190ac9f7c49b1036e20 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.