Triple
T7653621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Mississippi |
E173320
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | MS |
E79155
|
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: MS | Statement: [State of Mississippi, abbreviation, MS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MS Context triple: [State of Mississippi, abbreviation, MS]
-
A.
MS
chosen
MS is the official two-letter United States Postal Service abbreviation for the state of Mississippi.
-
B.
MS
MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
-
C.
MS
MS is a postgraduate Master of Science degree typically focused on advanced study and research in scientific or technical disciplines.
-
D.
MS
MS is the station code for Chennai Egmore, one of the major railway terminals in Chennai, India.
-
E.
MS
MS is the official vehicle registration code for the Brazilian state of Mato Grosso do Sul, whose capital is Campo Grande.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018c34a88190be6089a9105bd4b0 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89af47b9c819087d42f1b01c413fe |
completed | March 29, 2026, 3:22 a.m. |
Created at: March 27, 2026, 3:59 p.m.