Triple
T4825779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Kong |
E107820
|
entity |
| Predicate | iconicScene |
P43625
|
FINISHED |
| Object | climbing the Empire State Building |
—
|
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: climbing the Empire State Building | Statement: [King Kong, iconicScene, climbing the Empire State Building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconicScene Context triple: [King Kong, iconicScene, climbing the Empire State Building]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
iconicFeature
Indicates that something serves as a distinctive, widely recognized characteristic or symbol of another entity.
-
C.
notableCultImage
Indicates that an entity is associated with a significant or historically important religious or cultic image.
-
D.
isIconicIn
chosen
Indicates that something is widely recognized as a defining or emblematic example within a particular context, domain, or location.
-
E.
famousImage
Indicates that an image is widely recognized or well-known, typically due to its prominence, popularity, or cultural significance.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.