Triple
T2866186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piccadilly Circus Underground station |
E63442
|
entity |
| Predicate | hasMapType |
P42815
|
FINISHED |
| Object | Central London Underground station |
—
|
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: Central London Underground station | Statement: [Piccadilly Circus Underground station, hasMapType, Central London Underground station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMapType Context triple: [Piccadilly Circus Underground station, hasMapType, Central London Underground station]
-
A.
hasKeyType
Indicates that an entity possesses or is associated with a specific category or type of key.
-
B.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
hasStandardType
Indicates that something conforms to or is categorized under a defined standard classification or type.
-
D.
hasDictionaryType
Indicates that something is associated with or classified under a specific dictionary-defined type or category.
-
E.
hasCollectionType
Indicates that an entity is associated with or organized under a specific type or category of collection.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfbb7ed4819096ca65391077e2af |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:02 p.m.