Triple
T10147382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leland Tower |
E231737
|
entity |
| Predicate | hasLocalLandmarkStatus |
P13974
|
FINISHED |
| Object | prominent local landmark in Aurora |
—
|
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: prominent local landmark in Aurora | Statement: [Leland Tower, hasLocalLandmarkStatus, prominent local landmark in Aurora]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalLandmarkStatus Context triple: [Leland Tower, hasLocalLandmarkStatus, prominent local landmark in Aurora]
-
A.
isLocalLandmark
chosen
Indicates that something is recognized as a notable or significant landmark within a specific local area or community.
-
B.
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.
-
C.
hasLandmarkUnderManagement
Indicates that an entity is responsible for managing or overseeing a particular landmark.
-
D.
isLandmarkResultIn
Indicates that something serves as a landmark within, or as a result associated with, a particular context, area, or entity.
-
E.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec011c24819089b456fc8b9ed80c |
completed | April 2, 2026, 4:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:07 p.m.