Triple
T23943538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamamatsuchō |
E602853
|
entity |
| Predicate | hasOfficeTowers |
P39751
|
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: [Hamamatsuchō, hasOfficeTowers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeTowers Context triple: [Hamamatsuchō, hasOfficeTowers, yes]
-
A.
hasOfficeBuildings
chosen
Indicates that one entity possesses, controls, or is associated with one or more office buildings.
-
B.
isOfficeTower
Indicates that a structure functions primarily as a multi-story building used for office or commercial workspace purposes.
-
C.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
-
D.
hasCommunicationTowers
Indicates that one entity possesses, contains, or is equipped with communication towers used for transmitting or receiving signals.
-
E.
hasTower
Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
- F. None of above.
Provenance (3 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_69e2953e4924819093f1c24c03476b42 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d02bf38081909c99b98e04a8d2aa |
completed | April 29, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:10 p.m.