Triple
T14571064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evros regional unit |
E341913
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Feres
Feres is a town in northeastern Greece known for its historical significance and location near the Evros River and the Turkish border.
|
E1106401
|
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: Feres | Statement: [Evros regional unit, containsSettlement, Feres]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feres Context triple: [Evros regional unit, containsSettlement, Feres]
-
A.
Fikret
Fikret is a Turkish surname most notably associated with the influential poet and educator Tevfik Fikret, a leading figure in late Ottoman literature.
-
B.
Farud
Farud is a character in the Persian epic Shahnameh, known as the son of the legendary king Kay Kavus and for his tragic, heroic death in battle.
-
C.
Muzafer
Muzafer is the given name of Muzafer Sherif, a pioneering social psychologist best known for his work on group conflict and the Robbers Cave experiment.
-
D.
Fayiz
Fayiz is a masculine given name of Arabic origin, commonly used as a variant transliteration of the name Fayez.
-
E.
Faris
Faris is the surname of American actress and comedian Anna Faris, known for her roles in the Scary Movie film series and various comedy projects.
- 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: Feres Triple: [Evros regional unit, containsSettlement, Feres]
Generated description
Feres is a town in northeastern Greece known for its historical significance and location near the Evros River and the Turkish border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Feres Target entity description: Feres is a town in northeastern Greece known for its historical significance and location near the Evros River and the Turkish border.
-
A.
Fikret
Fikret is a Turkish surname most notably associated with the influential poet and educator Tevfik Fikret, a leading figure in late Ottoman literature.
-
B.
Farud
Farud is a character in the Persian epic Shahnameh, known as the son of the legendary king Kay Kavus and for his tragic, heroic death in battle.
-
C.
Muzafer
Muzafer is the given name of Muzafer Sherif, a pioneering social psychologist best known for his work on group conflict and the Robbers Cave experiment.
-
D.
Fayiz
Fayiz is a masculine given name of Arabic origin, commonly used as a variant transliteration of the name Fayez.
-
E.
Faris
Faris is the surname of American actress and comedian Anna Faris, known for her roles in the Scary Movie film series and various comedy projects.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f2121481908f2385637944785d |
completed | April 14, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aca591081908db149ec517a999b |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8bd70488819083f40c38575f3071 |
completed | May 8, 2026, 7:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8d4f2e848190a3c4c423c0ffed50 |
completed | May 8, 2026, 7:14 a.m. |
Created at: April 10, 2026, 1:23 a.m.