Triple
T22120016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manmad Junction railway station |
E546639
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object |
MMR
MMR is the Indian Railways station code for Manmad Junction, a major railway hub in Maharashtra, India.
|
E1519695
|
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: MMR | Statement: [Manmad Junction railway station, stationCode, MMR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MMR Context triple: [Manmad Junction railway station, stationCode, MMR]
-
A.
MMR
MMR is the Mumbai Metropolitan Region, a large urban agglomeration in and around Mumbai that encompasses multiple municipal corporations and towns in western India.
-
B.
MMCS
MMCS is the ICAO airport code for Abraham González International Airport serving Ciudad Juárez, Mexico.
-
C.
MM
MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
-
D.
MMV
MMV is the three-letter IATA airport code for McMinnville Municipal Airport in McMinnville, Oregon, United States.
-
E.
MMP
MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
- 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: MMR Triple: [Manmad Junction railway station, stationCode, MMR]
Generated description
MMR is the Indian Railways station code for Manmad Junction, a major railway hub in Maharashtra, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MMR Target entity description: MMR is the Indian Railways station code for Manmad Junction, a major railway hub in Maharashtra, India.
-
A.
MMR
MMR is the Mumbai Metropolitan Region, a large urban agglomeration in and around Mumbai that encompasses multiple municipal corporations and towns in western India.
-
B.
MMCS
MMCS is the ICAO airport code for Abraham González International Airport serving Ciudad Juárez, Mexico.
-
C.
MM
MM is a post-nominal abbreviation indicating that a person has been awarded the Military Medal for bravery in battle.
-
D.
MMV
MMV is the three-letter IATA airport code for McMinnville Municipal Airport in McMinnville, Oregon, United States.
-
E.
MMP
MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12951fcd48190841319cd879c15cb |
completed | April 28, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8f1fee748190be30339887981f99 |
completed | May 18, 2026, 4:01 a.m. |
| NEDg | Description generation | batch_6a0a924f9c0081909e33d6900675495b |
completed | May 18, 2026, 4:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a92f3ac948190893088711a300610 |
completed | May 18, 2026, 4:17 a.m. |
Created at: April 16, 2026, 8:31 p.m.