Triple
T25598877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grotta Gigante |
E641730
|
entity |
| Predicate | hasLightingInstallationYear |
P25196
|
FINISHED |
| Object | 1908 |
—
|
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: 1908 | Statement: [Grotta Gigante, hasLightingInstallationYear, 1908]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingInstallationYear Context triple: [Grotta Gigante, hasLightingInstallationYear, 1908]
-
A.
yearOfOriginalInstallation
chosen
Indicates the specific calendar year when something was first installed or put into initial operation.
-
B.
hasLightingImprovements
Indicates that an entity has enhancements or upgrades made to its lighting conditions or systems.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
lightDeactivatedYear
Indicates the year in which a light (or lighting system) was turned off, decommissioned, or otherwise taken out of active use.
-
E.
designYear
Indicates the year in which something was originally designed or conceived.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 21, 2026, 4:30 p.m.