Triple
T32584282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary–Romania border |
E832876
|
entity |
| Predicate | hasNearbyCityInHungary |
P85164
|
FINISHED |
| Object | Szeged |
—
|
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: Szeged | Statement: [Hungary–Romania border, hasNearbyCityInHungary, Szeged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCityInHungary Context triple: [Hungary–Romania border, hasNearbyCityInHungary, Szeged]
-
A.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
-
B.
hasNearbyMajorCityCountry
chosen
Indicates that an entity has a nearby major city located in the specified country.
-
C.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
D.
isInDirectionFromBudapest
Indicates that one entity is located in a specified compass or geographic direction when measured outward starting from Budapest.
-
E.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff53389a0481908b2baeb43c6294f0 |
completed | May 9, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69ff52e2b4b88190b38d160d771fe14b |
completed | May 9, 2026, 3:29 p.m. |
Created at: May 1, 2026, 1:04 a.m.