Triple
T38641125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TSMC N7P |
E938596
|
entity |
| Predicate | usesEUV |
P191471
|
FINISHED |
| Object | no |
—
|
LITERAL 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: no | Statement: [TSMC N7P, usesEUV, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEUV Context triple: [TSMC N7P, usesEUV, no]
-
A.
hasUEFACategory
Indicates that an entity is classified under a specific UEFA-defined category or tier.
-
B.
isProEuropean
Indicates support for European integration, institutions, or policies, or a generally favorable stance toward the European Union.
-
C.
usesEuropeanUnionDSTRules
Indicates that the action or process is governed by, or conforms to, the European Union’s Digital Services Act (DSA) rules and requirements.
-
D.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
E.
usedInEuropeanContext
Indicates that something is applied, referenced, or occurs specifically within a European geographical, cultural, legal, or institutional context.
- F. None of above. chosen
Provenance (4 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_69f76ed948ec81908ce7811608a8f359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:32 p.m.