Triple
T5364680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danishmendids |
E103100
|
entity |
| Predicate | territory |
P2160
|
FINISHED |
| Object | Malatya |
E285351
|
NE FINISHED |
How this triple was built (2 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: Malatya | Statement: [Danishmendids, territory, Malatya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malatya Context triple: [Danishmendids, territory, Malatya]
-
A.
Kilis
Kilis is a small Turkish city near the Syrian border known for its strategic location, cross-border trade, and distinctive regional cuisine.
-
B.
Karabük
Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
-
C.
Malatya Province
chosen
Malatya Province is a region in eastern Turkey known for its apricot production and as the birthplace of several notable Turkish figures.
-
D.
Amasya
Amasya is a historic city in northern Turkey, renowned for its Ottoman-era architecture, rock tombs of Pontic kings, and scenic setting along the Yeşilırmak River.
-
E.
Menemen
Menemen is a district and town in İzmir Province, Turkey, known for its agricultural production and as part of the greater İzmir metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865eb23481908d32fae4efd86efa |
completed | March 20, 2026, 5:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfe14608d88190ba2573da7cb783fe |
completed | March 22, 2026, 12:32 p.m. |
Created at: March 20, 2026, 2:02 p.m.