Triple
T13949989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Dizier |
E335494
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Dizier (personal name)
Dizier is a French given name of likely medieval origin, best known today for being the namesake of the town of Saint-Dizier in northeastern France.
|
E1071483
|
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: Dizier (personal name) | Statement: [Saint-Dizier, namedAfter, Dizier (personal name)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dizier (personal name) Context triple: [Saint-Dizier, namedAfter, Dizier (personal name)]
-
A.
Dizy
Dizy is a small municipality in the canton of Vaud in western Switzerland.
-
B.
Zierer
Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
-
C.
Desmers
Desmers is a surname variant of Demers, a French-origin family name found primarily in Francophone regions such as Quebec.
-
D.
Hirzer
Hirzer is a prominent mountain peak in the Sarntal Alps of South Tyrol, Italy, known for its panoramic hiking routes and scenic alpine views.
-
E.
Doische
Doische is a rural municipality in Wallonia, Belgium, known for its agricultural landscape and proximity to the French border.
- 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: Dizier (personal name) Triple: [Saint-Dizier, namedAfter, Dizier (personal name)]
Generated description
Dizier is a French given name of likely medieval origin, best known today for being the namesake of the town of Saint-Dizier in northeastern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dizier (personal name) Target entity description: Dizier is a French given name of likely medieval origin, best known today for being the namesake of the town of Saint-Dizier in northeastern France.
-
A.
Dizy
Dizy is a small municipality in the canton of Vaud in western Switzerland.
-
B.
Zierer
Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
-
C.
Desmers
Desmers is a surname variant of Demers, a French-origin family name found primarily in Francophone regions such as Quebec.
-
D.
Hirzer
Hirzer is a prominent mountain peak in the Sarntal Alps of South Tyrol, Italy, known for its panoramic hiking routes and scenic alpine views.
-
E.
Doische
Doische is a rural municipality in Wallonia, Belgium, known for its agricultural landscape and proximity to the French border.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e131c608190b4ffdbada24a3208 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1cca84881909c7733bbc2609eea |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba6af4ed881908cb4b79cfa40977c |
completed | May 6, 2026, 8:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba71a91fc8190b24185994673b33b |
completed | May 6, 2026, 8:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.