Triple
T15898931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bautzen district |
E385533
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Elstra
Elstra is a small town in the Bautzen district of the German federal state of Saxony.
|
E1183113
|
NE FINISHED |
How this triple was built (4 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: Elstra | Statement: [Bautzen district, containsTown, Elstra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elstra Context triple: [Bautzen district, containsTown, Elstra]
-
A.
Elst
Elst is a village in the Dutch municipality of Brakel, known as a small rural settlement in the province of Gelderland in the Netherlands.
-
B.
Elst
Elst is a town in the Netherlands that serves as a railway stop on the line between Arnhem and Nijmegen.
-
C.
Valstrona
Valstrona is a small municipality in Italy’s Piedmont region, situated in a mountainous valley known for its natural landscapes and traditional alpine villages.
-
D.
Eweland
Eweland is the cultural and historical homeland of the Ewe people, spanning parts of present-day Ghana, Togo, and Benin in West Africa.
-
E.
Ermera
Ermera is a mountainous municipality in central Timor-Leste known for its coffee production and significant Mambae-speaking population.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Elstra Triple: [Bautzen district, containsTown, Elstra]
Generated description
Elstra is a small town in the Bautzen district of the German federal state of Saxony.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elstra Target entity description: Elstra is a small town in the Bautzen district of the German federal state of Saxony.
-
A.
Elst
Elst is a village in the Dutch municipality of Brakel, known as a small rural settlement in the province of Gelderland in the Netherlands.
-
B.
Elst
Elst is a town in the Netherlands that serves as a railway stop on the line between Arnhem and Nijmegen.
-
C.
Valstrona
Valstrona is a small municipality in Italy’s Piedmont region, situated in a mountainous valley known for its natural landscapes and traditional alpine villages.
-
D.
Eweland
Eweland is the cultural and historical homeland of the Ewe people, spanning parts of present-day Ghana, Togo, and Benin in West Africa.
-
E.
Ermera
Ermera is a mountainous municipality in central Timor-Leste known for its coffee production and significant Mambae-speaking population.
- F. None of above. chosen
Provenance (5 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb04d4d1c819091d9b3357ca0deca |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb190ae4881909ac299dfa6e7d9b6 |
completed | May 9, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb25747148190bc96cf19acf85e29 |
completed | May 9, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:51 a.m.