Triple
T12337877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universidad station |
E294138
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | San Juan |
E274337
|
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: San Juan | Statement: [Universidad station, locatedIn, San Juan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Juan Context triple: [Universidad station, locatedIn, San Juan]
-
A.
San Juan
San Juan is a coastal municipality on Siquijor Island in the Philippines known for its beaches, dive spots, and laid-back tourist resorts.
-
B.
San Juan
San Juan is the largest city and main cultural, economic, and tourism hub of Puerto Rico, known for its historic colonial architecture and vibrant coastal setting.
-
C.
San Juan
chosen
San Juan is a highly urbanized city in Metro Manila, Philippines, known for its historical sites, dense residential and commercial areas, and role in the capital region’s urban core.
-
D.
San Juan
San Juan is a neighborhood within the municipality of Telde on the island of Gran Canaria in Spain’s Canary Islands.
-
E.
San Juan
San Juan is a coastal municipality in the Philippine province of Batangas known for its beaches, dive spots, and heritage sites.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f678698819091462b44ff3435f6 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b8ed1dc81908a0066d7cbfda086 |
completed | May 2, 2026, 7:07 p.m. |
Created at: April 8, 2026, 9:53 p.m.