Triple
T9908391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sepp Dietrich |
E185075
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Hawangen
Hawangen is a small municipality in the Unterallgäu district of Bavaria, Germany.
|
E829332
|
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: Hawangen | Statement: [Sepp Dietrich, placeOfBirth, Hawangen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hawangen Context triple: [Sepp Dietrich, placeOfBirth, Hawangen]
-
A.
Wanhatti
Wanhatti is a village in Suriname known as a Maroon settlement located within the country’s eastern Marowijne District.
-
B.
Haasgat
Haasgat is a fossil-bearing cave site in South Africa known for its valuable paleoanthropological and paleontological remains.
-
C.
Hienghène
Hienghène is a coastal commune in the North Province of New Caledonia, known for its dramatic limestone rock formations and cultural significance to the indigenous Kanak people.
-
D.
Hindkowans
Hindkowans are an Indo-Aryan ethnic group primarily associated with the Hindko language and concentrated in northern and central regions of Pakistan, especially in and around the Hazara area.
-
E.
Tongelre
Tongelre is a district in the Dutch city of Eindhoven, known for its mix of residential neighborhoods, green spaces, and former industrial areas.
- 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: Hawangen Triple: [Sepp Dietrich, placeOfBirth, Hawangen]
Generated description
Hawangen is a small municipality in the Unterallgäu district of Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hawangen Target entity description: Hawangen is a small municipality in the Unterallgäu district of Bavaria, Germany.
-
A.
Wanhatti
Wanhatti is a village in Suriname known as a Maroon settlement located within the country’s eastern Marowijne District.
-
B.
Haasgat
Haasgat is a fossil-bearing cave site in South Africa known for its valuable paleoanthropological and paleontological remains.
-
C.
Hienghène
Hienghène is a coastal commune in the North Province of New Caledonia, known for its dramatic limestone rock formations and cultural significance to the indigenous Kanak people.
-
D.
Hindkowans
Hindkowans are an Indo-Aryan ethnic group primarily associated with the Hindko language and concentrated in northern and central regions of Pakistan, especially in and around the Hazara area.
-
E.
Tongelre
Tongelre is a district in the Dutch city of Eindhoven, known for its mix of residential neighborhoods, green spaces, and former industrial areas.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50feb008190aa9c084f590c0ebd |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20daabd5881908b02da50a640766a |
completed | April 5, 2026, 7:22 a.m. |
| NEDg | Description generation | batch_69d20ef343a4819093b915a66c63fbaa |
completed | April 5, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d212d0ed108190bbde23439734618a |
completed | April 5, 2026, 7:44 a.m. |
Created at: March 30, 2026, 8:41 p.m.