Triple
T5013290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Hussein Bin Talal Mosque |
E112677
|
entity |
| Predicate | cityLandmarkType |
P16688
|
FINISHED |
| Object | religious landmark |
—
|
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: religious landmark | Statement: [King Hussein Bin Talal Mosque, cityLandmarkType, religious landmark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityLandmarkType Context triple: [King Hussein Bin Talal Mosque, cityLandmarkType, religious landmark]
-
A.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
-
B.
monumentType
Indicates the specific kind or category of monument that an entity is classified as.
-
C.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
D.
touristAttractionIn
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
-
E.
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.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730f12a481908a27c15dc73987c6 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.