Triple
T18008675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HotBot |
E430819
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | AltaVista |
—
|
NE NERFINISHED |
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: AltaVista | Statement: [HotBot, competitor, AltaVista]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AltaVista Context triple: [HotBot, competitor, AltaVista]
-
A.
AltaVista
chosen
AltaVista was one of the earliest and most popular web search engines of the 1990s, known for its fast, comprehensive internet search before being eclipsed by later competitors.
-
B.
Infoseek
Infoseek was an early web search engine and internet portal that gained prominence in the mid-1990s before being acquired and integrated into Disney’s online properties.
-
C.
Lycos
Lycos is an early web search engine and internet portal that was popular in the 1990s alongside rivals like AltaVista and Yahoo.
-
D.
Alexa Internet
Alexa Internet was a web traffic analysis and ranking company best known for providing website popularity metrics and analytics services before its shutdown in 2022.
-
E.
Goole
Goole is an inland port town in the East Riding of Yorkshire, England, known for its significant docks and role in regional maritime trade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b51e13788190bebbbdd7340e0982 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.