Triple
T16606235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christo |
E403453
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Wrapped Vespa |
E615270
|
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: Wrapped Vespa | Statement: [Christo, notableWork, Wrapped Vespa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wrapped Vespa Context triple: [Christo, notableWork, Wrapped Vespa]
-
A.
Vespa
chosen
Vespa is an iconic Italian brand of motor scooters known for its distinctive design and widespread popularity in urban transportation.
-
B.
Vespa
Vespa is a genus of large social wasps best known for including the true hornets found across Europe and Asia.
-
C.
Cotton Vespasian A.i
Cotton Vespasian A.i is a medieval manuscript volume from the Cotton Library collection, notable for preserving important early texts and documents.
-
D.
Lambretta
Lambretta is an iconic Italian line of motor scooters, renowned for its stylish design and popularity in post-war urban transport and scooter culture.
-
E.
Velaro
Velaro is a family of high-speed electric multiple unit trains developed by Siemens for use on major rail networks worldwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36090cf388190b401c55230912104 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075a8a6248190a9e2bb469d821c66 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:17 a.m.