Triple
T36628066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isleworth Mona Lisa |
E904229
|
entity |
| Predicate | hasCollection |
P426
|
FINISHED |
| Object |
Mona Lisa Foundation
The Mona Lisa Foundation is an organization dedicated to researching, promoting, and authenticating the so‑called "Isleworth Mona Lisa" as an earlier version of Leonardo da Vinci’s famous portrait.
|
E2192559
|
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: Mona Lisa Foundation | Statement: [Isleworth Mona Lisa, hasCollection, Mona Lisa Foundation]
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: Mona Lisa Foundation Triple: [Isleworth Mona Lisa, hasCollection, Mona Lisa Foundation]
Generated description
The Mona Lisa Foundation is an organization dedicated to researching, promoting, and authenticating the so‑called "Isleworth Mona Lisa" as an earlier version of Leonardo da Vinci’s famous portrait.
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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c4b2053c81909ce81e12c450f82c |
completed | May 3, 2026, 9:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3a09668388819085038ba372ba1ce8 |
completed | June 23, 2026, 4:19 a.m. |
| NEDg | Description generation | batch_6a3a0d894224819083922e4e45b567a5 |
completed | June 23, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3a116ce7588190a9eace8342ac564c |
completed | June 23, 2026, 4:54 a.m. |
Created at: May 3, 2026, 4:11 p.m.