Triple
T22348007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riverside Park |
E552445
|
entity |
| Predicate | mayBeLocatedNear |
P28981
|
FINISHED |
| Object | river or waterfront |
—
|
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: river or waterfront | Statement: [Riverside Park, mayBeLocatedNear, river or waterfront]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeLocatedNear Context triple: [Riverside Park, mayBeLocatedNear, river or waterfront]
-
A.
oftenLocatedNear
Indicates that one entity is frequently found in close physical proximity to another entity.
-
B.
partlyLocatedNear
Indicates that one entity is situated near another, but only a portion or subset of it lies within that nearby area.
-
C.
likelyLocatedIn
Indicates that an entity is probably situated within or associated with a particular location, though not with absolute certainty.
-
D.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
E.
possibleLocation
chosen
Indicates that an entity may be located at, or could plausibly occur in, a specified place or spatial 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157995bec819080b8d05fa88704ed |
completed | April 29, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.