Triple
T17017693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 63 Building |
E412863
|
entity |
| Predicate | hasNightViewReputation |
P124587
|
FINISHED |
| Object | Seoul skyline |
—
|
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: Seoul skyline | Statement: [63 Building, hasNightViewReputation, Seoul skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightViewReputation Context triple: [63 Building, hasNightViewReputation, Seoul skyline]
-
A.
hasViewReputation
Indicates that an entity holds a reputation or recognized standing specifically related to viewing, observing, or accessing something.
-
B.
hasNightViewSpot
chosen
Indicates that a location offers a suitable vantage point for viewing the scenery or cityscape at night.
-
C.
haveReputation
Indicates that an entity is recognized or regarded in a certain way by others, reflecting its perceived character, quality, or status.
-
D.
hasQuirkyReputation
Indicates that an entity is regarded by others as having an unusual, eccentric, or unconventional character or style.
-
E.
hasNotableReputation
Indicates that an entity is widely recognized or distinguished for a particular quality, achievement, or characteristic.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d480a58c8190a3912d26debb4311 |
completed | April 18, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.