Triple
T14553517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SaGoh 24/7 |
E341478
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Sago 24/7 |
E341478
|
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: Sago 24/7 | Statement: [SaGoh 24/7, hasAlternativeName, Sago 24/7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sago 24/7 Context triple: [SaGoh 24/7, hasAlternativeName, Sago 24/7]
-
A.
SaGoh 24/7
chosen
SaGoh 24/7 was a Christian punk/rock band that served as a precursor to and early project of members who later formed Anberlin.
-
B.
Sagàs
Sagàs is a small rural municipality in the Berguedà comarca of Catalonia, Spain, known for its agricultural landscape and traditional Catalan countryside.
-
C.
Soda Jungle
Soda Jungle is a large, forested and swamp-themed world in New Super Mario Bros. U known for its giant enemies and maze-like layout.
-
D.
Sendagi
Sendagi is a traditional residential neighborhood in Tokyo known for its preserved shitamachi atmosphere, narrow streets, and historic temples and shops.
-
E.
Fogagogo
Fogagogo is a small village located in Tualauta County on the island of Tutuila in American Samoa.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f00cec8190a7b6482d18b9a216 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab9a5ac81908779a3c8701353fa |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.