Triple
T5136508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meg March |
E115837
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | March |
E259249
|
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: March | Statement: [Meg March, familyName, March]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: March Context triple: [Meg March, familyName, March]
-
A.
March
March is a river in Central Europe that flows through countries including Austria, Slovakia, and the Czech Republic before joining the Danube.
-
B.
March
chosen
March is a fictional family surname most famously associated with the four sisters in Louisa May Alcott’s novel "Little Women."
-
C.
March
"March" is a critically acclaimed graphic memoir trilogy co-written by civil rights leader John Lewis and Andrew Aydin that chronicles Lewis's experiences in the American civil rights movement.
-
D.
MARCH
MARCH is a market town and civil parish in the Fenland district of Cambridgeshire, England, known historically as an important railway and river port.
-
E.
April
April is a spring month in the Gregorian calendar often associated with mild weather and the blooming of many flowers.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd785069108190bf9cfdc7d962d43f |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4d04b3c8190bfac5986e1bb89a5 |
completed | March 21, 2026, 4:18 p.m. |
Created at: March 20, 2026, 1:43 p.m.