Triple
T5921616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anita Borg |
E131710
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Transmeta |
E50342
|
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: Transmeta | Statement: [Anita Borg, employer, Transmeta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Transmeta Context triple: [Anita Borg, employer, Transmeta]
-
A.
Transmeta
chosen
Transmeta was an innovative semiconductor company best known for its low-power x86-compatible microprocessors and for employing Linux creator Linus Torvalds.
-
B.
Xicor
Xicor was a semiconductor company best known for designing and manufacturing non-volatile memory and analog integrated circuits.
-
C.
Oberon Microsystems
Oberon Microsystems is a Swiss software company known for its work on the Oberon family of languages and systems, including the development of the Component Pascal programming language.
-
D.
National Semiconductor
National Semiconductor was a major American semiconductor company known for its analog and mixed-signal integrated circuits, later acquired by Texas Instruments.
-
E.
Marvell Technology
Marvell Technology is a semiconductor company known for designing and developing data infrastructure and storage solutions for enterprise, cloud, automotive, and carrier markets.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03802ff4081908589236ba5cd196d |
completed | March 22, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c041d4f08190863141b037b1c05f |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 4 p.m.