Triple
T722315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utah Beach |
E14643
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object |
Carentan
Carentan is a small town in Normandy, France, known for its strategic role in the D-Day landings and subsequent World War II battles.
|
E99852
|
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: Carentan | Statement: [Utah Beach, nearbyTown, Carentan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carentan Context triple: [Utah Beach, nearbyTown, Carentan]
-
A.
Terrigal
Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
-
B.
Audenarde
Audenarde (Oudenaarde) is a historic city in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
C.
Mauregard
Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
-
D.
Edenborn
Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
-
E.
Bladon
Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
- 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: Carentan Triple: [Utah Beach, nearbyTown, Carentan]
Generated description
Carentan is a small town in Normandy, France, known for its strategic role in the D-Day landings and subsequent World War II battles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carentan Target entity description: Carentan is a small town in Normandy, France, known for its strategic role in the D-Day landings and subsequent World War II battles.
-
A.
Terrigal
Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
-
B.
Audenarde
Audenarde (Oudenaarde) is a historic city in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
-
C.
Mauregard
Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
-
D.
Edenborn
Edenborn is a science fiction novel by Nick Sagan that continues his post-apocalyptic series exploring genetic engineering and the future of humanity.
-
E.
Bladon
Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a591124c8190842e7ef18b064198 |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a79280fa5c819098397cc1b5c626c0 |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a79329fc2c81908dbf0627686ef47e |
completed | March 4, 2026, 2:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a793b89e38819090fd80afbb0fee96 |
completed | March 4, 2026, 2:06 a.m. |
Created at: March 1, 2026, 7:37 p.m.