Triple
T36191438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birkenhead |
E1046999
|
entity |
| Predicate | BirkenheadPark_notableFor |
P185052
|
FINISHED |
| Object | inspiration for design of Central Park in New York City |
—
|
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: inspiration for design of Central Park in New York City | Statement: [Birkenhead, BirkenheadPark_notableFor, inspiration for design of Central Park in New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BirkenheadPark_notableFor Context triple: [Birkenhead, BirkenheadPark_notableFor, inspiration for design of Central Park in New York City]
-
A.
oneOfOldestParksIn
Indicates that a park is among the oldest parks located within a specified place or region.
-
B.
oldestParkYearEstablished
Indicates the year in which the oldest park associated with a given entity was originally established.
-
C.
Pinner Fair
Indicates a fair or event taking place in, associated with, or named after Pinner.
-
D.
originalParkName
Indicates the relationship where a park is associated with its original or former official name.
-
E.
cityParkName
Indicates that the predicate specifies the name of a city park associated with a given entity.
- 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_69f76e3d4fbc81908c159c7beeb4ce00 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:08 p.m.