Triple
T2367267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GAESA |
E46010
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | GAESA |
E46010
|
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: GAESA | Statement: [GAESA, shortName, GAESA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GAESA Context triple: [GAESA, shortName, GAESA]
-
A.
GAESA
chosen
GAESA is a powerful Cuban military-owned business conglomerate that dominates key sectors of the country's economy, including tourism, retail, and real estate.
-
B.
Gyes
Gyes is an alternate name for Gyges, a figure from Greek mythology often associated with the Hecatoncheires, the hundred-handed giants.
-
C.
GAIS
GAIS is a Swedish sports club from Gothenburg best known for its professional football team competing in the national league system.
-
D.
EGA
EGA (Éléments de Géométrie Algébrique) is Alexander Grothendieck’s foundational multi-volume work that rigorously reformulated algebraic geometry using the language of schemes and sheaf theory.
-
E.
EGA
EGA is the common abbreviation for the Eagle, Globe, and Anchor emblem that symbolizes the United States Marine Corps.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc74b6bdc8190a12b2bcaa2dd7616 |
completed | March 7, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea89ae4688190be2e0825f0875ed3 |
completed | March 9, 2026, 11:01 a.m. |
Created at: March 4, 2026, 7:56 p.m.