Triple
T9900104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MVU |
E182260
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Elm |
E24476
|
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: Elm | Statement: [MVU, usedBy, Elm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elm Context triple: [MVU, usedBy, Elm]
-
A.
Elm
Elm is a civil parish and village in Cambridgeshire, England, known for its rural character and historic church.
-
B.
Elm
chosen
Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
-
C.
ELM
ELM is the commonly used abbreviation for the Estonian Literary Museum, a national research and memory institution dedicated to preserving and studying Estonia’s literary and folkloric heritage.
-
D.
ELM
ELM is the three-letter IATA airport code for Elmira/Corning Regional Airport in New York, United States.
-
E.
Maple
Maple is a comprehensive computer algebra system used for symbolic and numeric mathematics, modeling, and technical computing across education and research.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4e0705c8190bd17e36aff615cdd |
completed | April 2, 2026, 12:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb1b9534819093c5150f1ed8f685 |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:40 p.m.