Triple
T1192900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Street and Washington Avenue (Albany) |
E25601
|
entity |
| Predicate | hasNearbyPublicSpace |
P3449
|
FINISHED |
| Object | Capitol steps and plaza area |
—
|
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: Capitol steps and plaza area | Statement: [State Street and Washington Avenue (Albany), hasNearbyPublicSpace, Capitol steps and plaza area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyPublicSpace Context triple: [State Street and Washington Avenue (Albany), hasNearbyPublicSpace, Capitol steps and plaza area]
-
A.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
-
C.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
D.
hasAttractionNearby
chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
E.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd761ef08190b431b80f326d1ab2 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.