Triple
T31938859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pécel |
E815469
|
entity |
| Predicate | suburbanSettlementOf |
P15376
|
FINISHED |
| Object | Budapest |
—
|
NE NERFINISHED |
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: Budapest | Statement: [Pécel, suburbanSettlementOf, Budapest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanSettlementOf Context triple: [Pécel, suburbanSettlementOf, Budapest]
-
A.
suburb
Indicates that one place is a residential district or outlying area that is part of or adjacent to a larger city or town.
-
B.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
C.
isSuburbanCityOf
chosen
Indicates that one city is a suburban municipality that is part of, or closely associated with, a larger primary city or metropolitan area.
-
D.
isSuburbanNeighborhoodOf
Indicates that one area is a residential neighborhood located within or characteristic of the suburbs of another, typically larger, urban area.
-
E.
isUrbanSettlementIn
Indicates that an urban settlement (such as a city or town) is located within a specified larger geographic or administrative area.
- 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b26ea0348190b53ee3359c35d967 |
completed | May 3, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:05 a.m.