Triple
T664823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bury Line |
E12836
|
entity |
| Predicate | hasStop |
P17789
|
FINISHED |
| Object | Bury Metrolink stop |
—
|
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: Bury Metrolink stop | Statement: [Bury Line, hasStop, Bury Metrolink stop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStop Context triple: [Bury Line, hasStop, Bury Metrolink stop]
-
A.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
B.
isKeyStopOn
Indicates that a particular stop functions as a primary or significant stop along a specified route or service.
-
C.
hasStep
Indicates that one entity includes, is composed of, or is associated with a specific step or stage in a process involving another entity.
-
D.
hasStand
Indicates that an entity possesses, is equipped with, or is supported by a stand or base structure.
-
E.
hasTerminatingPlatforms
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd3d8fc8190866af5c76c08f486 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d16cff881908c8d2c3fe4d1d6fb |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.