Triple
T16251444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marsico Lung Institute |
E394513
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
MLI
MLI is the commonly used abbreviation for the Marsico Lung Institute, a research center focused on lung biology and respiratory diseases.
|
E1202451
|
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: MLI | Statement: [Marsico Lung Institute, abbreviation, MLI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLI Context triple: [Marsico Lung Institute, abbreviation, MLI]
-
A.
MLI
MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
-
B.
MLI
MLI is the IATA airport code for Quad Cities International Airport serving the Quad Cities region in Illinois and Iowa, United States.
-
C.
ML-2
ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
-
D.
ML-1
ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
-
E.
MSL
MSL is a NASA mission featuring the Curiosity rover, designed to explore Mars’ surface and assess its past and present habitability.
- 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: MLI Triple: [Marsico Lung Institute, abbreviation, MLI]
Generated description
MLI is the commonly used abbreviation for the Marsico Lung Institute, a research center focused on lung biology and respiratory diseases.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MLI Target entity description: MLI is the commonly used abbreviation for the Marsico Lung Institute, a research center focused on lung biology and respiratory diseases.
-
A.
MLI
MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
-
B.
MLI
MLI is the IATA airport code for Quad Cities International Airport serving the Quad Cities region in Illinois and Iowa, United States.
-
C.
ML-2
ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
-
D.
ML-1
ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
-
E.
MSL
MSL is a NASA mission featuring the Curiosity rover, designed to explore Mars’ surface and assess its past and present habitability.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24596e2208190ad9d9abfa6620ca1 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ee568a48190835ce76f84461044 |
completed | May 10, 2026, 4:51 a.m. |
| NEDg | Description generation | batch_6a0011995ff481908bbca9f9cfb41bf0 |
completed | May 10, 2026, 5:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0012669ff48190884367b92962a6d4 |
completed | May 10, 2026, 5:06 a.m. |
Created at: April 10, 2026, 5:04 a.m.