Triple
T7091462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Caen |
E165203
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lion-sur-Mer
Lion-sur-Mer is a coastal commune in northwestern France, situated on the English Channel in the Normandy region.
|
E640640
|
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: Lion-sur-Mer | Statement: [Arrondissement of Caen, contains, Lion-sur-Mer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lion-sur-Mer Context triple: [Arrondissement of Caen, contains, Lion-sur-Mer]
-
A.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
B.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
-
C.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
-
D.
Lagrenée
Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
-
E.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
- 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: Lion-sur-Mer Triple: [Arrondissement of Caen, contains, Lion-sur-Mer]
Generated description
Lion-sur-Mer is a coastal commune in northwestern France, situated on the English Channel in the Normandy region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lion-sur-Mer Target entity description: Lion-sur-Mer is a coastal commune in northwestern France, situated on the English Channel in the Normandy region.
-
A.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
B.
Crompond
Crompond is a small hamlet within the town of Yorktown in Westchester County, New York, known primarily as a residential community.
-
C.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
-
D.
Lagrenée
Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
-
E.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e53132288190b6da361d9c7218ab |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7948cb3d48190993134d709924e3d |
completed | March 28, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_69c7962ec0bc8190a9223ebb245d0914 |
completed | March 28, 2026, 8:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79709ed808190a9f09f5350ba2ffd |
completed | March 28, 2026, 8:53 a.m. |
Created at: March 27, 2026, 2:41 p.m.