Triple
T20139287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Link Aggregation Group |
E491115
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | LAG |
—
|
NE NERFINISHED |
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: LAG | Statement: [Link Aggregation Group, hasAbbreviation, LAG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LAG Context triple: [Link Aggregation Group, hasAbbreviation, LAG]
-
A.
LAG
chosen
LAG is the commonly used abbreviation for the LA Galaxy, a professional Major League Soccer club based in the Los Angeles area.
-
B.
LEG
LEG is the commonly used abbreviation for the Faculty of Law, Economics and Governance at Utrecht University, which combines legal, economic and governance disciplines.
-
C.
LEG
LEG is the International Maritime Organization’s Legal Committee, responsible for developing and maintaining international maritime law and liability conventions.
-
D.
LEG
LEG is the National Rail station code for Lea Green railway station in Merseyside, England.
-
E.
LAT
LAT is the Large Area Telescope, a high-energy gamma-ray detector aboard NASA's Fermi Gamma-ray Space Telescope used to study cosmic gamma-ray sources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667698a188190869c18b925dba2ed |
completed | April 20, 2026, 5:50 p.m. |
Created at: April 11, 2026, 11:32 p.m.