Triple
T6731914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lam Research |
E153652
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | ASML |
E352781
|
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: ASML | Statement: [Lam Research, competesWith, ASML]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ASML Context triple: [Lam Research, competesWith, ASML]
-
A.
ASML
chosen
ASML is a Dutch multinational company that is the world’s leading manufacturer of advanced photolithography equipment used in semiconductor chip production.
-
B.
Lam Research
Lam Research is a leading American semiconductor equipment company that supplies wafer fabrication tools and services to chip manufacturers worldwide.
-
C.
TSMC
TSMC (Taiwan Semiconductor Manufacturing Company) is the world’s largest dedicated semiconductor foundry, renowned for producing cutting-edge chips for major technology companies.
-
D.
Applied Materials
Applied Materials is a leading American corporation that supplies equipment, services, and software for the manufacture of semiconductors and other advanced electronic components.
-
E.
GlobalFoundries
GlobalFoundries is a major multinational semiconductor foundry that manufactures integrated circuits for a wide range of global technology companies.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16a30888190ae474d90bb71ac49 |
completed | March 27, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b0502d081909662028e2b40c7f3 |
completed | March 27, 2026, 10:56 p.m. |
Created at: March 27, 2026, 2:09 p.m.