Triple
T9262787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köterberg |
E222618
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Lügde
Lügde is a small historic town in North Rhine-Westphalia, Germany, known for its traditional Easter customs and scenic location near the Weser Uplands.
|
E788261
|
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: Lügde | Statement: [Köterberg, locatedNear, Lügde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lügde Context triple: [Köterberg, locatedNear, Lügde]
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Zahle
Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
-
C.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
-
D.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
E.
Lemvig
Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
- 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: Lügde Triple: [Köterberg, locatedNear, Lügde]
Generated description
Lügde is a small historic town in North Rhine-Westphalia, Germany, known for its traditional Easter customs and scenic location near the Weser Uplands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lügde Target entity description: Lügde is a small historic town in North Rhine-Westphalia, Germany, known for its traditional Easter customs and scenic location near the Weser Uplands.
-
A.
Havelberg
Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
-
B.
Zahle
Zahle is a prominent city in Lebanon’s Beqaa Valley, known for its historic architecture, vineyards, and role as a regional commercial and cultural center.
-
C.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
-
D.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
E.
Lemvig
Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
- 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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07189bc48190987315bd5d3ce4f1 |
completed | April 1, 2026, 11:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09c0526c48190aae93a70cfe5562c |
completed | April 4, 2026, 5:05 a.m. |
| NEDg | Description generation | batch_69d09d6cc45c8190b6cb44212ccfcbc8 |
completed | April 4, 2026, 5:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d09e2069048190ac22b738fa324771 |
completed | April 4, 2026, 5:14 a.m. |
Created at: March 30, 2026, 7:32 p.m.