Triple
T7192307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watts |
E167722
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Watson |
E91959
|
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: Watson | Statement: [Watts, relatedName, Watson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Watson Context triple: [Watts, relatedName, Watson]
-
A.
Watson
chosen
Watson is a common English surname borne by numerous notable figures, including scientists, artists, and public personalities.
-
B.
WATSON
WATSON is a close-up imaging camera on NASA’s Perseverance rover used to examine the fine details of Martian rocks and surface materials.
-
C.
Bixby
Bixby is Samsung's proprietary virtual assistant designed to enable voice control, smart device integration, and contextual assistance across the company's ecosystem of products.
-
D.
Thrun
Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
-
E.
Deep Blue
Deep Blue is a 2003 British nature documentary film, co-directed by Alastair Fothergill, that explores the world's oceans using spectacular underwater cinematography.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e901ea1481908a9e44f96dd4b553 |
completed | March 27, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf95a1a0819099d252f037c318c7 |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:50 p.m.