Triple
T20081587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walls, Mississippi |
E500013
|
entity |
| Predicate | stateAbbreviation |
P2461
|
FINISHED |
| Object | MS |
—
|
NE NERFINISHED |
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: MS | Statement: [Walls, Mississippi, stateAbbreviation, MS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MS Context triple: [Walls, Mississippi, stateAbbreviation, MS]
-
A.
MS
MS is the official vehicle registration code used on license plates for the German city of Münster.
-
B.
MS
MS is the New York Stock Exchange ticker symbol for Morgan Stanley, a leading global investment bank and financial services firm.
-
C.
MS
chosen
MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
-
D.
MS
MS is a postgraduate Master of Science degree typically focused on advanced study and research in scientific or technical disciplines.
-
E.
MS
MS is the two-letter IATA airline designator assigned to EgyptAir, the flag carrier of Egypt.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e665588a9c8190886b693b13a215a8 |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.