Triple
T15773389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centre Party (Germany) |
E382418
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Zentrum
Zentrum was a major Catholic-oriented political party in Germany that played a key role in German politics from the late 19th century through the Weimar Republic.
|
E1175601
|
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: Zentrum | Statement: [Centre Party (Germany), abbreviation, Zentrum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zentrum Context triple: [Centre Party (Germany), abbreviation, Zentrum]
-
A.
Centrum
Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
-
B.
Centrum
Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
-
C.
Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
-
D.
Centrs
Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
-
E.
Centrale
Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
- 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: Zentrum Triple: [Centre Party (Germany), abbreviation, Zentrum]
Generated description
Zentrum was a major Catholic-oriented political party in Germany that played a key role in German politics from the late 19th century through the Weimar Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zentrum Target entity description: Zentrum was a major Catholic-oriented political party in Germany that played a key role in German politics from the late 19th century through the Weimar Republic.
-
A.
Centrum
Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
-
B.
Centrum
Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
-
C.
Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
-
D.
Centrs
Centrs is the central district of Riga, Latvia, known for its historic architecture, cultural institutions, and commercial activity.
-
E.
Centrale
Centrale is a prestigious French engineering school renowned for its rigorous scientific curriculum and role in training elite engineers and industry leaders.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051976d248190adddd3db9f758e22 |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877e67b881908a67b9acc79d998f |
completed | May 9, 2026, 7:14 p.m. |
| NEDg | Description generation | batch_69ff88358e408190a8d7424fc495d4fa |
completed | May 9, 2026, 7:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff88f192a08190acbc2c3fc98c65c8 |
completed | May 9, 2026, 7:20 p.m. |
Created at: April 10, 2026, 4:47 a.m.