Triple
T10062625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumida Park |
E213023
|
entity |
| Predicate | hasApproxLengthAlongRiver |
P91898
|
FINISHED |
| Object | about 1 kilometer |
—
|
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: about 1 kilometer | Statement: [Sumida Park, hasApproxLengthAlongRiver, about 1 kilometer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxLengthAlongRiver Context triple: [Sumida Park, hasApproxLengthAlongRiver, about 1 kilometer]
-
A.
locatedInRiverArea
Indicates that one entity is situated within the geographic area occupied by, adjacent to, or directly associated with a particular river.
-
B.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
C.
waterwayLengthKilometres
Indicates the total length of a waterway, measured in kilometres.
-
D.
hasTownOnRiver
Indicates that a town is situated on or directly adjacent to a particular river.
-
E.
hasMajorTownOnRiver
Indicates that a major town is located on and directly associated with a particular river.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcfd3c6bc8190a21ed3566f9c08d1 |
completed | April 2, 2026, 2:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:58 p.m.