Triple
T16929282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rawanduz River |
E410659
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Soran
Soran is a town in the mountainous Kurdistan Region of northern Iraq, known as a gateway to nearby gorges, rivers, and natural attractions.
|
E1241412
|
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: Soran | Statement: [Rawanduz River, near, Soran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soran Context triple: [Rawanduz River, near, Soran]
-
A.
Arapgir
Arapgir is a historic town and district in eastern Turkey known for its traditional architecture, cultural heritage, and scenic location within Malatya Province.
-
B.
Arak
Arak is a major industrial city in central Iran known for its manufacturing sector and strategic economic importance.
-
C.
Saraghina
Saraghina is a memorable, sensual character from Federico Fellini’s film "8½," embodying the protagonist’s early, taboo experiences with desire and womanhood.
-
D.
Tarshiha
Tarshiha is an Arab town in northern Israel, known today as the Arab component of the mixed city of Ma'alot-Tarshiha.
-
E.
Anazarbus
Anazarbus was an important ancient city in the region of Cilicia, in what is now southern Turkey, known for its strategic location and impressive fortifications.
- 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: Soran Triple: [Rawanduz River, near, Soran]
Generated description
Soran is a town in the mountainous Kurdistan Region of northern Iraq, known as a gateway to nearby gorges, rivers, and natural attractions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Soran Target entity description: Soran is a town in the mountainous Kurdistan Region of northern Iraq, known as a gateway to nearby gorges, rivers, and natural attractions.
-
A.
Arapgir
Arapgir is a historic town and district in eastern Turkey known for its traditional architecture, cultural heritage, and scenic location within Malatya Province.
-
B.
Arak
Arak is a major industrial city in central Iran known for its manufacturing sector and strategic economic importance.
-
C.
Saraghina
Saraghina is a memorable, sensual character from Federico Fellini’s film "8½," embodying the protagonist’s early, taboo experiences with desire and womanhood.
-
D.
Tarshiha
Tarshiha is an Arab town in northern Israel, known today as the Arab component of the mixed city of Ma'alot-Tarshiha.
-
E.
Anazarbus
Anazarbus was an important ancient city in the region of Cilicia, in what is now southern Turkey, known for its strategic location and impressive fortifications.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf23873c8190bdc9121d6c3850e2 |
completed | April 18, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfdb6b608190af910e225d942d37 |
completed | May 10, 2026, 6:35 p.m. |
| NEDg | Description generation | batch_6a00d0ce499c81909bd4ec1c77ae0202 |
completed | May 10, 2026, 6:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d14b83d88190b3dbc124d5b33029 |
completed | May 10, 2026, 6:41 p.m. |
Created at: April 10, 2026, 5:30 a.m.