Triple
T38378403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jizzakh Region |
E893688
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Forish District
Forish District is an administrative district located within Uzbekistan's Jizzakh Region, known for its mountainous terrain and rural settlements.
|
E2277448
|
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: Forish District | Statement: [Jizzakh Region, hasSubdivision, Forish District]
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: Forish District Triple: [Jizzakh Region, hasSubdivision, Forish District]
Generated description
Forish District is an administrative district located within Uzbekistan's Jizzakh Region, known for its mountainous terrain and rural settlements.
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_69f76e4b1f748190a380696a16eae4a2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcccfd753881908786a1c94efc4e9f |
completed | May 7, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41ea79749c81908f83e810ec71e325 |
completed | June 29, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_6a41ebcc57788190b0480326b2904b79 |
completed | June 29, 2026, 3:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41ef7de8c08190948d909b8e5edbc1 |
completed | June 29, 2026, 4:07 a.m. |
Created at: May 3, 2026, 4:31 p.m.