Triple
T4434089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitsubishi Heavy Industries |
E95603
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
MHI
MHI is the commonly used abbreviation for Mitsubishi Heavy Industries, a major Japanese multinational engineering, electrical equipment, and heavy machinery company.
|
E440128
|
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: MHI | Statement: [Mitsubishi Heavy Industries, shortName, MHI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MHI Context triple: [Mitsubishi Heavy Industries, shortName, MHI]
-
A.
MH
MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
-
B.
MH
MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
-
C.
MH
MH is the official vehicle registration code assigned to the Indian state of Maharashtra.
-
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.
Mori
Mori is a Japanese surname shared by various notable individuals across fields such as entertainment, sports, and politics.
- 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: MHI Triple: [Mitsubishi Heavy Industries, shortName, MHI]
Generated description
MHI is the commonly used abbreviation for Mitsubishi Heavy Industries, a major Japanese multinational engineering, electrical equipment, and heavy machinery company.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MHI Target entity description: MHI is the commonly used abbreviation for Mitsubishi Heavy Industries, a major Japanese multinational engineering, electrical equipment, and heavy machinery company.
-
A.
MH
MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
-
B.
MH
MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
-
C.
MH
MH is the official vehicle registration code assigned to the Indian state of Maharashtra.
-
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.
Mori
Mori is a Japanese surname shared by various notable individuals across fields such as entertainment, sports, and politics.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35587bc048190aee8e0ed94b6e064 |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6137378dc8190900c8fda2693c4da |
completed | March 15, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_69b61439a86c8190849c5af718ddc647 |
completed | March 15, 2026, 2:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b614d6106c81908a601f540622f934 |
completed | March 15, 2026, 2:09 a.m. |
Created at: March 12, 2026, 11:31 p.m.