Triple
T10485798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 8 |
E247292
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Montgallet
Montgallet is a Paris Métro station in the 12th arrondissement, serving a residential and commercial area near Rue de Reuilly.
|
E866873
|
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: Montgallet | Statement: [Paris Métro Line 8, hasStation, Montgallet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montgallet Context triple: [Paris Métro Line 8, hasStation, Montgallet]
-
A.
Moreuil
Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
-
B.
Hautefort
Hautefort is a historic castle and commune in southwestern France, renowned as the medieval stronghold of the troubadour and nobleman Bertrand de Born.
-
C.
Bibertal
Bibertal is a municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Modane
Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
-
E.
Montagnana
Montagnana is a historic walled town in the Veneto region of northern Italy, renowned for its remarkably well-preserved medieval fortifications.
- 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: Montgallet Triple: [Paris Métro Line 8, hasStation, Montgallet]
Generated description
Montgallet is a Paris Métro station in the 12th arrondissement, serving a residential and commercial area near Rue de Reuilly.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Montgallet Target entity description: Montgallet is a Paris Métro station in the 12th arrondissement, serving a residential and commercial area near Rue de Reuilly.
-
A.
Moreuil
Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
-
B.
Hautefort
Hautefort is a historic castle and commune in southwestern France, renowned as the medieval stronghold of the troubadour and nobleman Bertrand de Born.
-
C.
Bibertal
Bibertal is a municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Modane
Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
-
E.
Montagnana
Montagnana is a historic walled town in the Veneto region of northern Italy, renowned for its remarkably well-preserved medieval fortifications.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5096988ec81908d7518b09256c145 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc7fc0cc8190922b7b783d37f542 |
completed | April 10, 2026, 11:18 a.m. |
| NEDg | Description generation | batch_69d8e8c81bdc8190b6b6dfe00025b514 |
completed | April 10, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d901e1ecf88190acd24a0e20462cb9 |
completed | April 10, 2026, 1:57 p.m. |
Created at: April 6, 2026, 12:23 p.m.