Triple
T9074691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esztergom Basilica |
E217455
|
entity |
| Predicate | hasGroundArea |
P55981
|
FINISHED |
| Object | about 5,600 square meters |
—
|
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: about 5,600 square meters | Statement: [Esztergom Basilica, hasGroundArea, about 5,600 square meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGroundArea Context triple: [Esztergom Basilica, hasGroundArea, about 5,600 square meters]
-
A.
hasBaseArea
chosen
Indicates that one entity has a base whose surface area is quantified or associated with another entity.
-
B.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
E.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c4026c8190b553aedb9f4beabb |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:12 p.m.