Triple
T10934301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taverny |
E258288
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object |
Tabernaciens
Tabernaciens are the inhabitants of Taverny, a commune in the northern suburbs of Paris, France.
|
E893729
|
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: Tabernaciens | Statement: [Taverny, hasDemonym, Tabernaciens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabernaciens Context triple: [Taverny, hasDemonym, Tabernaciens]
-
A.
Sparnacien
Sparnacien is the French demonym for an inhabitant of the town of Épernay in the Champagne region.
-
B.
In Taberna
In Taberna is the middle section of Carl Orff’s cantata Carmina Burana, depicting boisterous scenes of drinking, gambling, and revelry in a medieval tavern.
-
C.
Tiendesitas
Tiendesitas is a popular shopping and lifestyle complex in Pasig, Metro Manila, known for its Filipino-themed architecture, handicrafts, food, and live entertainment.
-
D.
Taverner
Taverner is a modern opera by British composer Peter Maxwell Davies that reimagines the life of the Renaissance composer John Taverner in a stark, expressionistic style.
-
E.
Le Hutin
Le Hutin is the French nickname of King Louis X of France, referring to his reputation as a quarrelsome or stubborn ruler.
- 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: Tabernaciens Triple: [Taverny, hasDemonym, Tabernaciens]
Generated description
Tabernaciens are the inhabitants of Taverny, a commune in the northern suburbs of Paris, France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tabernaciens Target entity description: Tabernaciens are the inhabitants of Taverny, a commune in the northern suburbs of Paris, France.
-
A.
Sparnacien
Sparnacien is the French demonym for an inhabitant of the town of Épernay in the Champagne region.
-
B.
In Taberna
In Taberna is the middle section of Carl Orff’s cantata Carmina Burana, depicting boisterous scenes of drinking, gambling, and revelry in a medieval tavern.
-
C.
Tiendesitas
Tiendesitas is a popular shopping and lifestyle complex in Pasig, Metro Manila, known for its Filipino-themed architecture, handicrafts, food, and live entertainment.
-
D.
Taverner
Taverner is a modern opera by British composer Peter Maxwell Davies that reimagines the life of the Renaissance composer John Taverner in a stark, expressionistic style.
-
E.
Le Hutin
Le Hutin is the French nickname of King Louis X of France, referring to his reputation as a quarrelsome or stubborn ruler.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ae073881909720febe9f5f296a |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2176328448190bbce6735ec97507a |
completed | April 17, 2026, 11:20 a.m. |
| NEDg | Description generation | batch_69e21d8aea2881908ac8f5225b8739c5 |
completed | April 17, 2026, 11:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e21eb18a1881908ded331db89063ed |
completed | April 17, 2026, 11:51 a.m. |
Created at: April 8, 2026, 9:23 p.m.