Triple
T10895805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reventador |
E257305
|
entity |
| Predicate | hasSpanishMeaning |
P96276
|
FINISHED |
| Object | the exploder |
—
|
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: the exploder | Statement: [Reventador, hasSpanishMeaning, the exploder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpanishMeaning Context triple: [Reventador, hasSpanishMeaning, the exploder]
-
A.
hasNameInSpanish
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
hasSignificantSpanishInfluence
Indicates that one entity has been strongly shaped or notably affected by Spanish culture, language, practices, or presence.
-
C.
hasSpanishLanguageVersion
Indicates that an entity has a corresponding version or representation available in the Spanish language.
-
D.
SpanishObjective
Indicates that an entity is the target or goal of an action, relation, or expression specifically in the Spanish language.
-
E.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish language.
- F. None of above. chosen
Provenance (4 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75d022f4c81909cd9ea27a9f0cd32 |
completed | April 9, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69d70d3943c881908895397eccc3e415 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101de31c819090707635f6790559 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:21 p.m.