Triple
T16252082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gil Mellé |
E394533
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mellé
Mellé is a French surname most notably borne by Gil Mellé, an American jazz musician and film and television composer.
|
E1202911
|
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: Mellé | Statement: [Gil Mellé, familyName, Mellé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mellé Context triple: [Gil Mellé, familyName, Mellé]
-
A.
Mèze
Mèze is a historic fishing and wine-producing town in southern France’s Hérault department, known for its oyster farming and location on the Mediterranean coast.
-
B.
Melle
Melle is a municipality in the Belgian province of East Flanders, known for its historic town center and proximity to the city of Ghent.
-
C.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
D.
Melle
Melle is a town in the German state of North Rhine-Westphalia, known for its location in the Osnabrück district and its mix of industrial and rural character.
-
E.
Mialet
Mialet is a commune in the Gard department of southern France, known for its scenic Cévennes landscape and proximity to notable caves and natural attractions.
- 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: Mellé Triple: [Gil Mellé, familyName, Mellé]
Generated description
Mellé is a French surname most notably borne by Gil Mellé, an American jazz musician and film and television composer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mellé Target entity description: Mellé is a French surname most notably borne by Gil Mellé, an American jazz musician and film and television composer.
-
A.
Mèze
Mèze is a historic fishing and wine-producing town in southern France’s Hérault department, known for its oyster farming and location on the Mediterranean coast.
-
B.
Melle
Melle is a municipality in the Belgian province of East Flanders, known for its historic town center and proximity to the city of Ghent.
-
C.
Melle
Melle is a town in Lower Saxony, Germany, known for its rural character, historical architecture, and role as a regional economic center.
-
D.
Melle
Melle is a town in the German state of North Rhine-Westphalia, known for its location in the Osnabrück district and its mix of industrial and rural character.
-
E.
Mialet
Mialet is a commune in the Gard department of southern France, known for its scenic Cévennes landscape and proximity to notable caves and natural attractions.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24597b74481908fdb8175628a57a1 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ee788f88190b16d267f1eee6d62 |
completed | May 10, 2026, 4:51 a.m. |
| NEDg | Description generation | batch_6a00113900c88190bf7f56ca4b16a84c |
completed | May 10, 2026, 5:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0011d98f708190805c84d63ed79aaa |
completed | May 10, 2026, 5:04 a.m. |
Created at: April 10, 2026, 5:04 a.m.