Triple
T5457607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | surface-barrier transistor |
E122517
|
entity |
| Predicate | hasBaseRegion |
P64159
|
FINISHED |
| Object | very thin germanium base |
—
|
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: very thin germanium base | Statement: [surface-barrier transistor, hasBaseRegion, very thin germanium base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaseRegion Context triple: [surface-barrier transistor, hasBaseRegion, very thin germanium base]
-
A.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
B.
hasGlobalRegion
Indicates that an entity is associated with or belongs to a specific global geographic region.
-
C.
isRegionOf
Indicates that one entity is a geographic or administrative region belonging to, contained within, or associated with another entity.
-
D.
hasBaseArea
Indicates that one entity has a base whose surface area is quantified or associated with another entity.
-
E.
basedOnRealRegion
Indicates that something is derived from, inspired by, or corresponds to an actual geographic or administrative region in the real world.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd927b0b4c81909d5e0f594822e3f9 |
completed | March 20, 2026, 6:31 p.m. |
Created at: March 20, 2026, 2:08 p.m.