Triple
T238978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USMIA |
E4885
|
entity |
| Predicate | UNLOCODELocationCode |
P1800
|
FINISHED |
| Object |
MIA
MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
|
E30755
|
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: MIA | Statement: [USMIA, UNLOCODELocationCode, MIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MIA Context triple: [USMIA, UNLOCODELocationCode, MIA]
-
A.
MIA
MIA is the standard three-letter abbreviation used to represent the Miami Marlins Major League Baseball team.
-
B.
Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
-
C.
Junior M.A.F.I.A.
Junior M.A.F.I.A. is a Brooklyn-based hip hop group formed and mentored by The Notorious B.I.G., known for its mid-1990s mafioso-themed rap and launching the career of Lil' Kim.
-
D.
MEEI
MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
-
E.
MAB
MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
- 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: MIA Triple: [USMIA, UNLOCODELocationCode, MIA]
Generated description
MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MIA Target entity description: MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
-
A.
MIA
MIA is the standard three-letter abbreviation used to represent the Miami Marlins Major League Baseball team.
-
B.
Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
-
C.
Junior M.A.F.I.A.
Junior M.A.F.I.A. is a Brooklyn-based hip hop group formed and mentored by The Notorious B.I.G., known for its mid-1990s mafioso-themed rap and launching the career of Lil' Kim.
-
D.
MEEI
MEEI is a renowned specialty hospital in Boston focused on ophthalmology and otolaryngology, affiliated with Harvard Medical School.
-
E.
MAB
MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ccda0ac8190a44f4bebfc0aba67 |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36735dff881908ed9cefbf6f5e09d |
completed | Feb. 28, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69a367d82e9c8190ae1bcc99232a24fa |
completed | Feb. 28, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3689a2970819087306bff495a4a3a |
completed | Feb. 28, 2026, 10:13 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.