Triple
T11619464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magic Fountain of Montjuïc |
E275598
|
entity |
| Predicate | hasLightingTechnology |
P1280
|
FINISHED |
| Object | LED lights |
—
|
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: LED lights | Statement: [Magic Fountain of Montjuïc, hasLightingTechnology, LED lights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingTechnology Context triple: [Magic Fountain of Montjuïc, hasLightingTechnology, LED lights]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
hasLightingEffect
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
C.
usesBacklightTechnology
Indicates that one entity employs backlight technology to illuminate or enhance the visibility of another entity or its display.
-
D.
hasLightingImprovements
Indicates that an entity has enhancements or upgrades made to its lighting conditions or systems.
-
E.
hasLightEmittingElement
Indicates that one entity includes or is equipped with a component that emits light.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a047758081908191c1d564409d9a |
completed | April 10, 2026, 7:01 a.m. |
| PD | Predicate disambiguation | batch_69d85dd6503c819081f9045e9d5c4f3f |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.