Triple
T14082279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chennai Egmore railway station |
E338895
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | MS |
E338895
|
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: [Chennai Egmore railway station, hasAbbreviation, MS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MS Context triple: [Chennai Egmore railway station, hasAbbreviation, 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
MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
-
D.
MS
chosen
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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5f759c81909bfd60ab35b0937b |
completed | April 14, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdefe88b481908b3dca1f019e7809 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:21 p.m.