Triple
T8816146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FMG |
E209781
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | FMG |
E209781
|
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: FMG | Statement: [FMG, abbreviation, FMG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FMG Context triple: [FMG, abbreviation, FMG]
-
A.
FMG
chosen
FMG is the Faculty of Social and Behavioural Sciences at the University of Amsterdam, encompassing disciplines such as psychology, sociology, political science, and communication science.
-
B.
FMC
FMC is the Spanish acronym for the Federation of Cuban Women, a mass organization in Cuba dedicated to advancing women's rights and gender equality.
-
C.
FMU
FMU is a public university in Florence, South Carolina, known for its liberal arts and professional programs.
-
D.
FMF
FMF is the commonly used abbreviation for the Mexican Football Federation, the governing body of professional and amateur soccer in Mexico.
-
E.
FNM
FNM was the former stock ticker symbol for Fannie Mae, the U.S. government-sponsored enterprise that provides liquidity and stability to the mortgage market.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc600bd8a88190ad891a96201d796b |
completed | April 1, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6fb898388190b96242ff41599250 |
completed | April 3, 2026, 7:43 a.m. |
Created at: March 30, 2026, 6:45 p.m.