Triple
T1539804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana |
E32838
|
entity |
| Predicate | isoCode |
P189
|
FINISHED |
| Object | US-LA |
E32838
|
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: US-LA | Statement: [Louisiana, isoCode, US-LA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US-LA Context triple: [Louisiana, isoCode, US-LA]
-
A.
US-MS
US-MS is the ISO 3166-2 code representing the U.S. state of Mississippi.
-
B.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
-
C.
US-ME
US-ME is the ISO 3166-2 code representing the U.S. state of Maine.
-
D.
Louisiana
chosen
Louisiana is a U.S. state in the Deep South known for its unique Creole and Cajun cultures, the city of New Orleans, and its rich musical and culinary traditions.
-
E.
USAIS
USAIS is the U.S. Army’s primary institution for training, educating, and developing infantry soldiers and leaders.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9083c942481909168394b6674d82b |
completed | March 5, 2026, 4:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad30997d408190916f16d31bcc35b4 |
completed | March 8, 2026, 8:17 a.m. |
Created at: March 4, 2026, 7:26 p.m.