Triple
T6735840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamm |
E153750
|
entity |
| Predicate | hasDistricts |
P1679
|
FINISHED |
| Object |
Uentrop
Uentrop is a district of the German city of Hamm in North Rhine-Westphalia, known for its mix of residential areas and industrial facilities.
|
E614932
|
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: Uentrop | Statement: [Hamm, hasDistricts, Uentrop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uentrop Context triple: [Hamm, hasDistricts, Uentrop]
-
A.
Enodia
Enodia is an epithet of the Greek goddess Hecate that emphasizes her role as a protector and guide along roads, thresholds, and liminal spaces.
-
B.
Uatsdin
Uatsdin is the modern revival of the indigenous Ossetian ethnic religion, centered on traditional deities, rituals, and ancestral customs of the Ossetian people.
-
C.
Zenta
Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
-
D.
Entissar
Entissar is an Arabic feminine given name commonly used in the Middle East and North Africa, meaning "victory" or "triumph."
-
E.
Balkhausen
Balkhausen is a district within the town of Kerpen in North Rhine-Westphalia, Germany.
- 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: Uentrop Triple: [Hamm, hasDistricts, Uentrop]
Generated description
Uentrop is a district of the German city of Hamm in North Rhine-Westphalia, known for its mix of residential areas and industrial facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Uentrop Target entity description: Uentrop is a district of the German city of Hamm in North Rhine-Westphalia, known for its mix of residential areas and industrial facilities.
-
A.
Enodia
Enodia is an epithet of the Greek goddess Hecate that emphasizes her role as a protector and guide along roads, thresholds, and liminal spaces.
-
B.
Uatsdin
Uatsdin is the modern revival of the indigenous Ossetian ethnic religion, centered on traditional deities, rituals, and ancestral customs of the Ossetian people.
-
C.
Zenta
Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
-
D.
Entissar
Entissar is an Arabic feminine given name commonly used in the Middle East and North Africa, meaning "victory" or "triumph."
-
E.
Balkhausen
Balkhausen is a district within the town of Kerpen in North Rhine-Westphalia, Germany.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d18369d88190a73349075462202b |
completed | March 27, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b09b97c8190a5a538571b6909f0 |
completed | March 27, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69c70bda97f08190bc6dab7177341876 |
completed | March 27, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70c51e0148190be64afb56690b34f |
completed | March 27, 2026, 11:01 p.m. |
Created at: March 27, 2026, 2:09 p.m.