Triple
T35954038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Washington Street, Chicago |
E1039807
|
entity |
| Predicate | hasAdjacentLandmarkType |
P120316
|
FINISHED |
| Object | high-rise office tower |
—
|
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: high-rise office tower | Statement: [West Washington Street, Chicago, hasAdjacentLandmarkType, high-rise office tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentLandmarkType Context triple: [West Washington Street, Chicago, hasAdjacentLandmarkType, high-rise office tower]
-
A.
adjacentLandmark
Indicates that one landmark is located directly next to or very near another landmark, with no significant separation between them.
-
B.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
C.
hasFormerNearbyLandmark
Indicates that an entity previously had a nearby landmark that no longer exists or no longer holds the same status or relevance.
-
D.
hasNearbyLandscapeType
Indicates that one entity is located close to, or in the vicinity of, a particular type of landscape.
-
E.
hasNearbySiteType
chosen
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
- 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_69f76e25ea488190b7cee970b3e70382 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
Created at: May 3, 2026, 4:07 p.m.