Triple
T21013676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SoFA District |
E517614
|
entity |
| Predicate | isTouristAttractionOf |
P7335
|
FINISHED |
| Object | San Jose |
E1776
|
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 Jose | Statement: [SoFA District, isTouristAttractionOf, San Jose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Jose Context triple: [SoFA District, isTouristAttractionOf, San Jose]
-
A.
San Jose
chosen
San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
-
B.
San Jose
San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
-
C.
San Jose
San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
-
D.
San Jose
San Jose is a barangay (village-level administrative division) of the municipality of Ternate in the province of Cavite, Philippines.
-
E.
San Jose
San Jose is a coastal municipality in the province of Occidental Mindoro in the Philippines, known as a commercial and transportation hub for the region.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc41d57881908b9ab17d1844a8d0 |
completed | April 21, 2026, 4:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a096dacc2788190b6f6be0962936781 |
completed | May 17, 2026, 7:26 a.m. |
Created at: April 16, 2026, 1:54 p.m.