Triple
T33021900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belmont Harbor |
E844933
|
entity |
| Predicate | hasNearbyParkFeature |
P199955
|
FINISHED |
| Object | open green space |
—
|
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: open green space | Statement: [Belmont Harbor, hasNearbyParkFeature, open green space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyParkFeature Context triple: [Belmont Harbor, hasNearbyParkFeature, open green space]
-
A.
hasNearbyParkEntrance
Indicates that one location is situated close to an entrance of a park.
-
B.
hasParkingNearby
Indicates that a location has one or more parking facilities or spaces available within a close surrounding area.
-
C.
isNeighborhoodParkOf
Indicates that a park is located within and serves as a local recreational area for a specific neighborhood.
-
D.
hasNearbyStatePark
Indicates that a location is situated close to at least one designated state park.
-
E.
locatedInParkVicinity
Indicates that an entity is situated in the area immediately surrounding or near a park.
- F. None of above. chosen
Provenance (4 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff65987ff88190b09be64f7c0e1da9 |
completed | May 9, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69ff6525b0548190bef7a9f009e00bb8 |
completed | May 9, 2026, 4:47 p.m. |
| PDg | Predicate description generation | batch_69ff659717708190bb56714d1b261063 |
completed | May 9, 2026, 4:49 p.m. |
Created at: May 1, 2026, 1:23 a.m.