Triple
T35999116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durance River canal system |
E1041078
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
Canal de Carpentras
The Canal de Carpentras is an irrigation canal in southeastern France that distributes water from the Durance River to farmland and communities in the Vaucluse region.
|
E2172477
|
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: Canal de Carpentras | Statement: [Durance River canal system, component, Canal de Carpentras]
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: Canal de Carpentras Triple: [Durance River canal system, component, Canal de Carpentras]
Generated description
The Canal de Carpentras is an irrigation canal in southeastern France that distributes water from the Durance River to farmland and communities in the Vaucluse region.
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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac8118148190bef390a078185205 |
completed | May 3, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a390d329f4c8190a2ecbd89db95ef5b |
completed | June 22, 2026, 10:23 a.m. |
| NEDg | Description generation | batch_6a390dc2e07c8190a0d3f095f67478b1 |
completed | June 22, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a39109ebb2c8190b1f85279a7506977 |
completed | June 22, 2026, 10:38 a.m. |
Created at: May 3, 2026, 4:07 p.m.