Triple
T23859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire State Building |
E472
|
entity |
| Predicate | lightingFeature |
P1280
|
FINISHED |
| Object | multi-colored tower 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: multi-colored tower lights | Statement: [Empire State Building, lightingFeature, multi-colored tower lights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingFeature Context triple: [Empire State Building, lightingFeature, multi-colored tower lights]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
featuredIn
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
-
C.
surfaceType
Indicates the kind or classification of surface associated with an entity or interaction.
-
D.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
envisionedAs
Indicates that one entity is mentally pictured, imagined, or conceived in terms of another entity or role.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.