Triple
T32925612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metra zone D |
E842262
|
entity |
| Predicate | distanceBasis |
P205200
|
FINISHED |
| Object | distance from downtown Chicago |
—
|
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: distance from downtown Chicago | Statement: [Metra zone D, distanceBasis, distance from downtown Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceBasis Context triple: [Metra zone D, distanceBasis, distance from downtown Chicago]
-
A.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
B.
distanceFromBol
Indicates the measured distance between an entity and a specified beginning-of-line (BOL) reference point.
-
C.
distanceFromBabylon
Indicates the spatial distance between a given location or object and the city of Babylon.
-
D.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
E.
distanceMetric
Indicates a quantitative measure of how far apart two entities are within a given space or according to a specified metric.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:20 a.m.