Triple
T5456482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bien de Interés Cultural |
E122489
|
entity |
| Predicate | isSpanishTermFor |
P12773
|
FINISHED |
| Object | Asset of Cultural Interest |
—
|
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: Asset of Cultural Interest | Statement: [Bien de Interés Cultural, isSpanishTermFor, Asset of Cultural Interest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSpanishTermFor Context triple: [Bien de Interés Cultural, isSpanishTermFor, Asset of Cultural Interest]
-
A.
hasNameInSpanish
chosen
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec language.
-
C.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish language.
-
D.
SpanishEditionURL
Indicates the web address where the Spanish-language edition or version of something can be accessed.
-
E.
officialNameInSpanish
Indicates the officially recognized name of an entity 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.