Triple
T278675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KG |
E5304
|
entity |
| Predicate | contrastedWith |
P278
|
FINISHED |
| Object | LG |
E14246
|
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: LG | Statement: [KG, contrastedWith, LG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LG Context triple: [KG, contrastedWith, LG]
-
A.
LG
LG is the post-nominal abbreviation used by members of the prestigious British chivalric Order of the Garter.
-
B.
LG Electronics
chosen
LG Electronics is a South Korean multinational electronics company known for producing a wide range of consumer electronics, home appliances, and mobile devices.
-
C.
Samsung
Samsung is a South Korean multinational conglomerate best known globally for its smartphones, consumer electronics, and advanced semiconductor technologies.
-
D.
American Appliance Company
American Appliance Company was the original name of the U.S. technology and defense contractor later known as Raytheon Company.
-
E.
HMD
HMD is the commonly used abbreviation for Holocaust Memorial Day in the United Kingdom, a national day of remembrance for the victims of the Holocaust and subsequent genocides.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dee7830819087f153769a8496b9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a394a2b1a081909bb78499544984da |
completed | March 1, 2026, 1:21 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.