Triple
T1159683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaume Plensa |
E24464
|
entity |
| Predicate | creatorOf |
P806
|
FINISHED |
| Object | Echo |
E131716
|
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: Echo | Statement: [Jaume Plensa, creatorOf, Echo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Echo Context triple: [Jaume Plensa, creatorOf, Echo]
-
A.
Echo
Echo is Amazon’s smart speaker line that integrates the Alexa voice assistant to control smart-home devices, play media, and provide information via voice commands.
-
B.
Echo
chosen
Echo is a monumental outdoor sculpture by Spanish artist Jaume Plensa, known for its elongated, meditative female head form.
-
C.
Soundwave
Soundwave is a Decepticon from the Transformers franchise, known for his cold, calculating loyalty to Megatron and his ability to deploy smaller cassette-like minions for espionage and combat.
-
D.
Whisper
Whisper is an open-source automatic speech recognition system by OpenAI that transcribes and translates spoken language with high accuracy across many languages.
-
E.
Audion
Audion is an early triode vacuum tube invented by Lee de Forest that enabled the amplification of electrical signals and was crucial to the development of radio and electronics.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcad47a08190895769611798f67f |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac667d2bdc8190b7d797683a4d3fe8 |
completed | March 7, 2026, 5:55 p.m. |
Created at: March 1, 2026, 7:45 p.m.