Triple
T15265531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conflent |
E364891
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Serdinya
Serdinya is a small commune in the Pyrénées-Orientales department of southern France, situated in the historic region of Conflent in the eastern Pyrenees.
|
E1147499
|
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: Serdinya | Statement: [Conflent, containsTown, Serdinya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serdinya Context triple: [Conflent, containsTown, Serdinya]
-
A.
Serdi
The Serdi were an ancient Thracian tribe that inhabited the region around present-day Sofia, Bulgaria, giving their name to the Roman city of Serdica.
-
B.
Torda
Torda is an alternative historical name for the Romanian city of Turda, known for its rich history and notable salt mine in Transylvania.
-
C.
Gevaş
Gevaş is a town and district in eastern Turkey, situated on the southern shore of Lake Van in Van Province.
-
D.
Serhedi
Serhedi is a regional dialect of Kurmanji Kurdish spoken in parts of the Kurdish-inhabited areas of the Middle East.
-
E.
Sarnıç
Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
- 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: Serdinya Triple: [Conflent, containsTown, Serdinya]
Generated description
Serdinya is a small commune in the Pyrénées-Orientales department of southern France, situated in the historic region of Conflent in the eastern Pyrenees.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serdinya Target entity description: Serdinya is a small commune in the Pyrénées-Orientales department of southern France, situated in the historic region of Conflent in the eastern Pyrenees.
-
A.
Serdi
The Serdi were an ancient Thracian tribe that inhabited the region around present-day Sofia, Bulgaria, giving their name to the Roman city of Serdica.
-
B.
Torda
Torda is an alternative historical name for the Romanian city of Turda, known for its rich history and notable salt mine in Transylvania.
-
C.
Gevaş
Gevaş is a town and district in eastern Turkey, situated on the southern shore of Lake Van in Van Province.
-
D.
Serhedi
Serhedi is a regional dialect of Kurmanji Kurdish spoken in parts of the Kurdish-inhabited areas of the Middle East.
-
E.
Sarnıç
Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00851c5b88190a296b6a105d3ee30 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee600340c8190a1888d35c2c1bc86 |
completed | May 9, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fee714cf6c81908dc4427590eeae85 |
completed | May 9, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feeae4731081909964bd8b1ea3dd7a |
completed | May 9, 2026, 8:05 a.m. |
Created at: April 10, 2026, 3:14 a.m.