Triple
T10214894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsushita Electric Industrial Co. |
E242414
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
MEI
MEI is an abbreviation for Matsushita Electric Industrial Co., the Japanese electronics company better known globally by its Panasonic brand.
|
E850022
|
NE FINISHED |
How this triple was built (4 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: MEI | Statement: [Matsushita Electric Industrial Co., alsoKnownAs, MEI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MEI Context triple: [Matsushita Electric Industrial Co., alsoKnownAs, MEI]
-
A.
MEI
MEI is a climate index that quantifies the strength and phase of the El Niño–Southern Oscillation by combining multiple atmospheric and oceanic variables over the tropical Pacific.
-
B.
MEI
MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
-
C.
MEEI
MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
-
D.
MITEI
MITEI is the Massachusetts Institute of Technology’s multidisciplinary research and education hub focused on advancing energy technologies, policy, and innovation for a low-carbon future.
-
E.
MEB
MEB is the IATA airport code for Essendon Airport, a public airport serving the Melbourne region in Victoria, Australia.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MEI Triple: [Matsushita Electric Industrial Co., alsoKnownAs, MEI]
Generated description
MEI is an abbreviation for Matsushita Electric Industrial Co., the Japanese electronics company better known globally by its Panasonic brand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MEI Target entity description: MEI is an abbreviation for Matsushita Electric Industrial Co., the Japanese electronics company better known globally by its Panasonic brand.
-
A.
MEI
MEI is the vehicle registration code for the German town of Meissen in the state of Saxony.
-
B.
MEI
MEI is a climate index that quantifies the strength and phase of the El Niño–Southern Oscillation by combining multiple atmospheric and oceanic variables over the tropical Pacific.
-
C.
MEEI
MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
-
D.
MITEI
MITEI is the Massachusetts Institute of Technology’s multidisciplinary research and education hub focused on advancing energy technologies, policy, and innovation for a low-carbon future.
-
E.
MEB
MEB is the IATA airport code for Essendon Airport, a public airport serving the Melbourne region in Victoria, Australia.
- F. None of above. chosen
Provenance (5 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa273bdc8190bc4cf67a7923cebc |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652f1ffb88190986ea53749fc5e03 |
completed | April 8, 2026, 1:06 p.m. |
| NEDg | Description generation | batch_69d656d55ff481909b84c033aa0f0fc2 |
completed | April 8, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d658a657488190ab08071889af4fb6 |
completed | April 8, 2026, 1:31 p.m. |
Created at: April 6, 2026, 11:04 a.m.