Triple
T29600339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eger |
E754423
|
entity |
| Predicate | historicSettlementNameFor |
P76172
|
FINISHED |
| Object | Cheb |
—
|
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: Cheb | Statement: [Eger, historicSettlementNameFor, Cheb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicSettlementNameFor Context triple: [Eger, historicSettlementNameFor, Cheb]
-
A.
historicalSettlementType
Indicates the type or category of settlement an entity was historically classified as (e.g., village, town, city) during a past period.
-
B.
historicalTownName
chosen
Indicates that the object is a former or historical name by which the town (subject) was previously known.
-
C.
historicAdministrativeCentre
Indicates that a place served as the main administrative or governmental center for a region or jurisdiction during a past historical period.
-
D.
modernNameOfServedSettlement
Indicates that the object is the current, modern name of the settlement that is or was served by the subject (e.g., a facility, infrastructure, or service).
-
E.
historicallyASettlementOn
Indicates that one place historically existed as a settlement located on or at the site of another place.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
Created at: April 28, 2026, 6:21 p.m.