Triple
T4429381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Cebu |
E95287
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Toledo City |
E261525
|
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: Toledo City | Statement: [Province of Cebu, hasCity, Toledo City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toledo City Context triple: [Province of Cebu, hasCity, Toledo City]
-
A.
Toledo City
chosen
Toledo City is a coastal component city on the western side of Cebu Island in the Philippines, known for its mining industry and port facilities.
-
B.
Toledo
Toledo is a historic Spanish city renowned for its medieval architecture, cultural heritage, and role as a major political and religious center in Spain’s history.
-
C.
Toledo
Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
-
D.
Havana, Ohio
Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
-
E.
Vandalia, Ohio
Vandalia, Ohio is a suburban city in Montgomery County that serves as a key community in the Dayton metropolitan area of the Miami Valley 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35568767c819084d5e18b56a4745e |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6136caa248190a84423cede1908c3 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:30 p.m.