Triple
T13768756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altındağ |
E330819
|
entity |
| Predicate | containsPart |
P35
|
FINISHED |
| Object |
Aydınlıkevler
Aydınlıkevler is a neighborhood in the Altındağ district of Ankara, Turkey, known primarily as a residential area.
|
E1059878
|
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: Aydınlıkevler | Statement: [Altındağ, containsPart, Aydınlıkevler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aydınlıkevler Context triple: [Altındağ, containsPart, Aydınlıkevler]
-
A.
Orhaneli
Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
-
B.
Kalyeserye
Kalyeserye is a popular romantic-comedy mini-series segment from the Philippine noontime show Eat Bulaga! that famously featured the love team "AlDub" and became a cultural phenomenon.
-
C.
Hudur
Hudur is a key urban center in southwestern Somalia that serves as an administrative and commercial hub for the surrounding region.
-
D.
Aydin
Aydin is a given name used as a variant of Aidan, found in various cultures and spellings.
-
E.
Korkuteli
Korkuteli is a town and district in southwestern Turkey known for its agricultural production and cooler highland climate compared to the coastal areas of Antalya 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: Aydınlıkevler Triple: [Altındağ, containsPart, Aydınlıkevler]
Generated description
Aydınlıkevler is a neighborhood in the Altındağ district of Ankara, Turkey, known primarily as a residential area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aydınlıkevler Target entity description: Aydınlıkevler is a neighborhood in the Altındağ district of Ankara, Turkey, known primarily as a residential area.
-
A.
Orhaneli
Orhaneli is a town and district in northwestern Turkey known for its rural character and location within Bursa Province.
-
B.
Kalyeserye
Kalyeserye is a popular romantic-comedy mini-series segment from the Philippine noontime show Eat Bulaga! that famously featured the love team "AlDub" and became a cultural phenomenon.
-
C.
Hudur
Hudur is a key urban center in southwestern Somalia that serves as an administrative and commercial hub for the surrounding region.
-
D.
Aydin
Aydin is a given name used as a variant of Aidan, found in various cultures and spellings.
-
E.
Korkuteli
Korkuteli is a town and district in southwestern Turkey known for its agricultural production and cooler highland climate compared to the coastal areas of Antalya 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0233ecc48190b934f085d2501eb1 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a866e7cc8190a0381f4469193b6e |
completed | May 3, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69f7a9f5549c81908a1a0b080acc3396 |
completed | May 3, 2026, 8:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7aafceea881908737a3d7613db2d5 |
completed | May 3, 2026, 8:07 p.m. |
Created at: April 9, 2026, 10:10 p.m.