Triple
T36272752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mera |
E892718
|
entity |
| Predicate | cantonSeat |
P25046
|
FINISHED |
| Object | Mera Canton |
—
|
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: Mera Canton | Statement: [Mera, cantonSeat, Mera Canton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cantonSeat Context triple: [Mera, cantonSeat, Mera Canton]
-
A.
municipalitySeat
Indicates that one entity serves as the administrative center or capital (seat) of a municipality.
-
B.
capitalLocation
Indicates the relationship in which a place serves as the capital city or administrative center of a given political or geographic entity.
-
C.
isCapitalMunicipalityOf
Indicates that a municipality serves as the official capital (administrative center) of a specified larger region, such as a state, province, or country.
-
D.
mainSeatOf
chosen
Indicates that one entity serves as the primary or central seat (e.g., of government, administration, or authority) for another entity.
-
E.
capitalAreaOf
Indicates that a specified area value represents the total land or geographic size of the capital city of a given entity.
- 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.