Triple
T37297542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bornes Massif |
E925844
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Plateau des Glières
Plateau des Glières is a high alpine plateau in the French Alps renowned both for its natural beauty and as a historic center of French Resistance activity during World War II.
|
E2240343
|
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: Plateau des Glières | Statement: [Bornes Massif, contains, Plateau des Glières]
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: Plateau des Glières Triple: [Bornes Massif, contains, Plateau des Glières]
Generated description
Plateau des Glières is a high alpine plateau in the French Alps renowned both for its natural beauty and as a historic center of French Resistance activity during World War II.
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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb5aee1d7481908223f437c70a4538 |
completed | May 6, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40d65f938c8190a86ba2f907dbc5db |
completed | June 28, 2026, 8:07 a.m. |
| NEDg | Description generation | batch_6a40d7e634b48190a99da2222ebc04bd |
completed | June 28, 2026, 8:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40d96828bc819080bc6fa16564db9f |
completed | June 28, 2026, 8:20 a.m. |
Created at: May 3, 2026, 4:16 p.m.