Triple
T33585900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Grignan |
E860278
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object |
House of Adhémar
The House of Adhémar was a prominent medieval noble family from southeastern France, historically influential in the region of Grignan and the Drôme.
|
E2058645
|
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: House of Adhémar | Statement: [Château de Grignan, associatedWith, House of Adhémar]
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: House of Adhémar Triple: [Château de Grignan, associatedWith, House of Adhémar]
Generated description
The House of Adhémar was a prominent medieval noble family from southeastern France, historically influential in the region of Grignan and the Drôme.
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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f77444248190b8e6aac2d3b932e2 |
completed | May 3, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a35afea2c98819083a11ad9743884aa |
completed | June 19, 2026, 9:08 p.m. |
| NEDg | Description generation | batch_6a35b1f646048190ba8d1af99bbb84be |
completed | June 19, 2026, 9:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a35b25e77a081908d21e6ce1fc57742 |
completed | June 19, 2026, 9:19 p.m. |
Created at: May 1, 2026, 1:40 a.m.