Triple
T391889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miami Dolphins |
E8898
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | MIA |
E30755
|
NE FINISHED |
How this triple was built (2 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: [Miami Dolphins, abbreviation, MIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MIA Context triple: [Miami Dolphins, abbreviation, MIA]
-
A.
MIA
chosen
MIA is the UN/LOCODE designation for Miami, a major coastal city and transportation hub in the U.S. state of Florida.
-
B.
MIA
MIA is the standard three-letter abbreviation used to represent the Miami Marlins Major League Baseball team.
-
C.
Mina
Mina is a valley and neighborhood near Mecca in Saudi Arabia that serves as a major site for key Hajj rituals, including the symbolic stoning of the devil.
-
D.
Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
-
E.
Milyan
Milyan is an extinct Anatolian Indo-European language once spoken in southwestern Asia Minor, known primarily from a small corpus of inscriptions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec7492288190bf33c9c869a0710f |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a405f74cd08190a2e165506638607c |
completed | March 1, 2026, 9:25 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.