Triple
T3638128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vizio |
E77119
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Hisense |
E58092
|
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: Hisense | Statement: [Vizio, hasCompetitor, Hisense]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hisense Context triple: [Vizio, hasCompetitor, Hisense]
-
A.
Midea
Midea is an important archaeological site in Greece that was a fortified citadel of the Mycenaean civilization.
-
B.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
-
C.
LG Electronics
LG Electronics is a South Korean multinational electronics company known for producing a wide range of consumer electronics, home appliances, and mobile devices.
-
D.
TCL Corporation
chosen
TCL Corporation is a major Chinese electronics company best known globally for manufacturing televisions and other consumer electronics.
-
E.
Vizio
Vizio is an American consumer electronics company best known for its affordable flat-screen televisions and home entertainment products.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f23298481909d313d6b3f8013cd |
completed | March 13, 2026, 5:53 p.m. |
Created at: March 8, 2026, 3:24 p.m.