Triple
T31693324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillsdale station |
E808851
|
entity |
| Predicate | gradeSeparatedFrom |
P96763
|
FINISHED |
| Object |
42nd Avenue
42nd Avenue is a roadway in the Hillsdale area of San Mateo, California, that runs adjacent to and beneath the grade-separated Hillsdale Caltrain station.
|
E2013799
|
NE FINISHED |
How this triple was built (3 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: 42nd Avenue | Statement: [Hillsdale station, gradeSeparatedFrom, 42nd Avenue]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 42nd Avenue Triple: [Hillsdale station, gradeSeparatedFrom, 42nd Avenue]
Generated description
42nd Avenue is a roadway in the Hillsdale area of San Mateo, California, that runs adjacent to and beneath the grade-separated Hillsdale Caltrain station.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradeSeparatedFrom Context triple: [Hillsdale station, gradeSeparatedFrom, 42nd Avenue]
-
A.
gradeSeparated
chosen
Indicates that two intersecting transportation routes are physically separated by different elevation levels so they do not cross at the same grade.
-
B.
gradeWithin
Indicates that one value’s grade or level falls within a specified range or interval relative to another.
-
C.
gradeCategory
Indicates the classification of a grade into a broader category or level (such as letter grade, performance band, or pass/fail group).
-
D.
gradeIn
Indicates that an entity has a particular grade or score within a specified course, assignment, or evaluation context.
-
E.
grades
Indicates that one entity evaluates and assigns a score or level of performance to another entity.
- F. None of above.
Provenance (6 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_69f348ddcbc48190950cabcc25ff29b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3485e8ce748190ae2623cdd2e9a7a4 |
completed | June 18, 2026, 11:57 p.m. |
| NEDg | Description generation | batch_6a34875b66608190bbe006cf51c2e2c3 |
completed | June 19, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3487bf3eb88190bc41cbcf4f7cc24a |
completed | June 19, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:09 p.m.