Triple
T805278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AltaVista |
E17416
|
entity |
| Predicate | acquiredBy |
P347
|
FINISHED |
| Object | Compaq |
E20318
|
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: Compaq | Statement: [AltaVista, acquiredBy, Compaq]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Compaq Context triple: [AltaVista, acquiredBy, Compaq]
-
A.
Compaq
chosen
Compaq was a major American computer company best known for its popular line of personal computers and for being one of the largest PC manufacturers before its acquisition by Hewlett-Packard.
-
B.
Hewlett-Packard
Hewlett-Packard is a pioneering American technology company known for its innovations in computing, printers, and enterprise IT solutions.
-
C.
Dell
Dell is a major American technology company best known for designing, manufacturing, and selling personal computers, servers, and related IT products and services worldwide.
-
D.
Lenovo
Lenovo is a multinational technology company best known for manufacturing and selling personal computers, laptops, smartphones, and other consumer electronics worldwide.
-
E.
Micros Systems
Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4aabff3d88190bec4299fa0d87df0 |
completed | March 1, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7928af9d0819095b28e738a0f60dd |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.