Triple
T24465722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cognac region |
E616960
|
entity |
| Predicate | primaryRiver |
P165
|
FINISHED |
| Object |
Charente River
The Charente River is a major waterway in southwestern France renowned for flowing through the heart of the Cognac-producing region and supporting its historic brandy industry.
|
E298483
|
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: Charente River | Statement: [Cognac region, primaryRiver, Charente River]
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: Charente River Triple: [Cognac region, primaryRiver, Charente River]
Generated description
The Charente River is a major waterway in southwestern France renowned for flowing through the heart of the Cognac-producing region and supporting its historic brandy industry.
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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2993ecd988190991598832b29a131 |
completed | April 29, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1032e3084481908d2c088d7afe03f8 |
completed | May 22, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_6a1033ece8248190bc0ee7fa4976848d |
completed | May 22, 2026, 10:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10348fb55c819087a28d4a7280589c |
completed | May 22, 2026, 10:48 a.m. |
Created at: April 18, 2026, 2:19 a.m.