Triple
T26041843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harlem Valley Rail Trail (segment) |
E647711
|
entity |
| Predicate | hasModeOfUse |
P119199
|
FINISHED |
| Object | pedestrian |
—
|
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: pedestrian | Statement: [Harlem Valley Rail Trail (segment), hasModeOfUse, pedestrian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModeOfUse Context triple: [Harlem Valley Rail Trail (segment), hasModeOfUse, pedestrian]
-
A.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
B.
availableInMode
chosen
Indicates that something can be used, accessed, or functions within a specified mode or operational setting.
-
C.
usesModality
Indicates that an action, communication, or process is carried out through or characterized by a particular modality (such as visual, auditory, tactile, or another mode of expression or operation).
-
D.
hasWorkingMode
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
-
E.
hasSecondaryUsage
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
- 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_69e77e8c88f08190858c4c81bd2e1b9a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 22, 2026, 9:08 a.m.