Triple
T5557747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ask Jeeves |
E145688
|
entity |
| Predicate | hasBrandName |
P40804
|
FINISHED |
| Object | Ask Jeeves |
E145688
|
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: Ask Jeeves | Statement: [Ask Jeeves, hasBrandName, Ask Jeeves]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ask Jeeves Context triple: [Ask Jeeves, hasBrandName, Ask Jeeves]
-
A.
Ask Jeeves (search engine brand name)
chosen
Ask Jeeves was an early web search engine brand best known for its question‑and‑answer style interface featuring a virtual butler character.
-
B.
Ask
Ask is a small village located in the municipality of Ringerike in Buskerud county, Norway.
-
C.
alexa.com
alexa.com was a popular web analytics and traffic ranking website that provided insights into the popularity and audience metrics of millions of websites worldwide.
-
D.
HotBot
HotBot is an early web search engine that gained prominence in the late 1990s for its fast and customizable search capabilities.
-
E.
Yahoo! Answers
Yahoo! Answers was a community-driven question-and-answer platform where users could ask questions and receive answers from other users across a wide range of topics.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffe12cc81908186f28ace0f4d82 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0283ebcd081909c86ced90c44266f |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:36 p.m.