Triple
T232505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moro Rock |
E4437
|
entity |
| Predicate | hasParkingArea |
P1708
|
FINISHED |
| Object | Moro Rock parking lot |
—
|
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: Moro Rock parking lot | Statement: [Moro Rock, hasParkingArea, Moro Rock parking lot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkingArea Context triple: [Moro Rock, hasParkingArea, Moro Rock parking lot]
-
A.
hasParking
chosen
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
C.
parkSection
Indicates a relationship where a specific area or subsection belongs to, is contained within, or is designated as part of a larger park.
-
D.
hasParkDistrict
Indicates that an entity is associated with, located within, or administered by a specific park district.
-
E.
hasParkAlongBank
Indicates that a park is located adjacent to or running alongside the bank of a water body.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25f14f72081908182e76300b59358 |
completed | Feb. 28, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69a25b5c8c888190b5544e687736b373 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.