Triple
T7900265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lighthouse at Two Lights |
E183432
|
entity |
| Predicate | depictsLightingCondition |
P42109
|
FINISHED |
| Object | sunlight |
—
|
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: sunlight | Statement: [The Lighthouse at Two Lights, depictsLightingCondition, sunlight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsLightingCondition Context triple: [The Lighthouse at Two Lights, depictsLightingCondition, sunlight]
-
A.
illuminationCondition
chosen
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
B.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
C.
lightType
Indicates the specific category or kind of light associated with an entity or lighting setup.
-
D.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
-
E.
lightingDependsOn
Indicates that the state or behavior of lighting is determined or influenced by another specified factor or condition.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a3dc2208190a6fea93b60b8daca |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:02 p.m.