Triple
T36774372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fronhausen |
E908573
|
entity |
| Predicate | distanceToGießen |
P205039
|
FINISHED |
| Object | approximately 20 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 20 kilometres | Statement: [Fronhausen, distanceToGießen, approximately 20 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGießen Context triple: [Fronhausen, distanceToGießen, approximately 20 kilometres]
-
A.
distanceToStuttgart
Indicates the measured distance between a given entity’s location and the city of Stuttgart.
-
B.
distanceToKarlsruhe
Indicates the spatial distance between a given entity and the location of Karlsruhe.
-
C.
distanceToWuerzburg
Indicates the spatial distance between a given location or entity and the city of Würzburg.
-
D.
distanceToKassel
Indicates the spatial distance between a given entity and the location Kassel.
-
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.