Triple
T2803599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenwich railway station |
E53999
|
entity |
| Predicate | hasDLRInterchange |
P43319
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Greenwich railway station, hasDLRInterchange, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDLRInterchange Context triple: [Greenwich railway station, hasDLRInterchange, yes]
-
A.
isInterchangeWith
Indicates that two entities can be substituted or exchanged for one another without loss of function, value, or compatibility.
-
B.
isInterchange
Indicates that two entities can be substituted or exchanged for one another without affecting the relevant system, function, or outcome.
-
C.
hasBusInterchange
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
-
D.
isInterchangeBetween
Indicates a relationship where something serves as a point or medium through which two or more entities can exchange or transfer items, information, or traffic between each other.
-
E.
hasNearbyInterchange
Indicates that one location has a transportation interchange (such as a junction or transfer point) situated close to it.
- 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_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde2ec2ac8190bd702ad3eafb6aed |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd059f308190853191f6ffe2bc6f |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde2cdcc48190827195d3ae70aa19 |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 9:59 p.m.