Triple
T17914458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manavgat |
E447889
|
entity |
| Predicate | hasBeachArea |
P1922
|
FINISHED |
| Object |
Evrenseki
Evrenseki is a coastal resort area and neighborhood near Manavgat in Turkey’s Antalya Province, known for its sandy Mediterranean beaches and tourist hotels.
|
E1296189
|
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: Evrenseki | Statement: [Manavgat, hasBeachArea, Evrenseki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evrenseki Context triple: [Manavgat, hasBeachArea, Evrenseki]
-
A.
Leysse
Leysse is a river in the Savoie department of southeastern France that flows through Chambéry before emptying into Lac du Bourget.
-
B.
Talgut
Talgut is a locality or neighborhood that forms part of the municipality of Ittigen in the canton of Bern, Switzerland.
-
C.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
D.
Karakilise
Karakilise is a historical name for the city now known as Ağrı in eastern Turkey.
-
E.
Orhaneli
Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
- 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: Evrenseki Triple: [Manavgat, hasBeachArea, Evrenseki]
Generated description
Evrenseki is a coastal resort area and neighborhood near Manavgat in Turkey’s Antalya Province, known for its sandy Mediterranean beaches and tourist hotels.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Evrenseki Target entity description: Evrenseki is a coastal resort area and neighborhood near Manavgat in Turkey’s Antalya Province, known for its sandy Mediterranean beaches and tourist hotels.
-
A.
Leysse
Leysse is a river in the Savoie department of southeastern France that flows through Chambéry before emptying into Lac du Bourget.
-
B.
Talgut
Talgut is a locality or neighborhood that forms part of the municipality of Ittigen in the canton of Bern, Switzerland.
-
C.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
D.
Karakilise
Karakilise is a historical name for the city now known as Ağrı in eastern Turkey.
-
E.
Orhaneli
Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30461848190b932a45807329216 |
completed | April 19, 2026, 9:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03212ab44c81909120d15c283d1c3c |
completed | May 12, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_6a03220af8dc8190aec1469d5c3d63be |
completed | May 12, 2026, 12:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a032277e9c8819084a9d4c6f559bebc |
completed | May 12, 2026, 12:52 p.m. |
Created at: April 10, 2026, 10:20 a.m.