Triple
T11321312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mira-Bhayandar |
E268099
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
MBMC
MBMC is the municipal governing body responsible for civic administration and infrastructure in the Mira-Bhayandar region of Maharashtra, India.
|
E919064
|
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: MBMC | Statement: [Mira-Bhayandar, shortName, MBMC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MBMC Context triple: [Mira-Bhayandar, shortName, MBMC]
-
A.
MCBH
MCBH is a major United States Marine Corps installation located on the island of Oahu in Hawaii, supporting Marine, Navy, and joint military operations in the Pacific region.
-
B.
MBZ
MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
-
C.
MBTS
MBTS is a Southern Baptist seminary in Kansas City, Missouri, focused on training pastors, missionaries, and church leaders for Christian ministry.
-
D.
BMVI
BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
-
E.
BMVI
BMVI is an EU funding instrument focused on strengthening border management and visa policy implementation across member states.
- 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: MBMC Triple: [Mira-Bhayandar, shortName, MBMC]
Generated description
MBMC is the municipal governing body responsible for civic administration and infrastructure in the Mira-Bhayandar region of Maharashtra, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MBMC Target entity description: MBMC is the municipal governing body responsible for civic administration and infrastructure in the Mira-Bhayandar region of Maharashtra, India.
-
A.
MCBH
MCBH is a major United States Marine Corps installation located on the island of Oahu in Hawaii, supporting Marine, Navy, and joint military operations in the Pacific region.
-
B.
MBZ
MBZ is the widely used acronym for Mohamed bin Zayed Al Nahyan, the President of the United Arab Emirates and Ruler of Abu Dhabi.
-
C.
MBTS
MBTS is a Southern Baptist seminary in Kansas City, Missouri, focused on training pastors, missionaries, and church leaders for Christian ministry.
-
D.
BMVI
BMVI is the abbreviation for Germany’s former Federal Ministry responsible for transport policy and digital infrastructure development.
-
E.
BMVI
BMVI is an EU funding instrument focused on strengthening border management and visa policy implementation across member states.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9dff37081909622623e66e17ccd |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e525e2549081909ec99e4c7006fd66 |
completed | April 19, 2026, 6:58 p.m. |
| NEDg | Description generation | batch_69e52c82b6108190aec9b6e9d726f803 |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e531b079708190ac9e19127d36a848 |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:32 p.m.