Triple
T1884990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borland |
E39942
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Borland International |
E39942
|
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: Borland International | Statement: [Borland, formerName, Borland International]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borland International Context triple: [Borland, formerName, Borland International]
-
A.
Borland
chosen
Borland was a prominent software company best known for its influential development tools and programming environments, particularly during the 1980s and 1990s.
-
B.
Embarcadero
Embarcadero is a historic waterfront district in San Francisco known for its piers, ferry terminal, and scenic promenade along the bay.
-
C.
Commodore International
Commodore International was a pioneering computer and electronics company best known for creating popular home computers like the Commodore 64 and the Amiga line.
-
D.
Embarcadero Technologies
Embarcadero Technologies is a software company best known for developing database tools and the Delphi rapid application development environment for Windows and cross-platform applications.
-
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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb11eb2d0819088d67b1cfc772049 |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf61413081909c0e840590aaf631 |
completed | March 8, 2026, 8:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.