Triple
T36774371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fronhausen |
E908573
|
entity |
| Predicate | distanceToMarburg |
P205038
|
FINISHED |
| Object | approximately 15 kilometres |
—
|
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: approximately 15 kilometres | Statement: [Fronhausen, distanceToMarburg, approximately 15 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMarburg Context triple: [Fronhausen, distanceToMarburg, approximately 15 kilometres]
-
A.
distanceToMagdeburg
Indicates the spatial distance between a given entity’s location and the city of Magdeburg.
-
B.
distanceToWuerzburg
Indicates the spatial distance between a given location or entity and the city of Würzburg.
-
C.
distanceToHamburg
Indicates the spatial distance between a given entity’s location and the city of Hamburg.
-
D.
distanceToMünster
Indicates the spatial distance between a given entity and the location Münster.
-
E.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
- F. None of above. chosen
Provenance (4 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_69f76e798aa08190ace31098d1b13e9f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:12 p.m.