Triple
T25381238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterContinental Bucharest Hotel |
E631392
|
entity |
| Predicate | isCityLandmark |
P124480
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [InterContinental Bucharest Hotel, isCityLandmark, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCityLandmark Context triple: [InterContinental Bucharest Hotel, isCityLandmark, true]
-
A.
isUrbanLandmark
chosen
Indicates that a place or structure is recognized as a notable or significant landmark within an urban environment.
-
B.
isRegionalLandmark
Indicates that a place or structure is widely recognized as a notable or iconic landmark within a specific geographic region.
-
C.
hasLandmarkCity
Indicates that a particular landmark is located within or associated with a specific city.
-
D.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
E.
primaryCityLandmarkOf
Indicates that a landmark is a principal or defining landmark associated with a specific city.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f55e6016908190957eb98ac70ec280 |
completed | May 2, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
Created at: April 21, 2026, 1:46 p.m.