Triple
T15016428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chains of Navarre |
E377969
|
entity |
| Predicate | languageName_es |
P12773
|
FINISHED |
| Object | Cadenas de Navarra |
—
|
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: Cadenas de Navarra | Statement: [Chains of Navarre, languageName_es, Cadenas de Navarra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageName_es Context triple: [Chains of Navarre, languageName_es, Cadenas de Navarra]
-
A.
hasNameInSpanish
chosen
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
SpanishObjective
Indicates that an entity is the target or goal of an action, relation, or expression specifically in the Spanish language.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
SpanishEditionURL
Indicates the web address where the Spanish-language edition or version of something can be accessed.
-
E.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7633fcc8190b2231f43252bc46f |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:55 a.m.