Triple
T12541515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiclayo |
E299848
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Pimentel |
E611665
|
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: Pimentel | Statement: [Chiclayo, hasPort, Pimentel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pimentel Context triple: [Chiclayo, hasPort, Pimentel]
-
A.
Pimentel
chosen
Pimentel is a surname of Portuguese and Spanish origin borne by various notable individuals across fields such as science, politics, and the arts.
-
B.
Palau Aguilar
Palau Aguilar is a historic medieval palace in Barcelona’s Gothic Quarter that serves as the main building of the Picasso Museum.
-
C.
Mabini
Mabini is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
-
D.
Mabini
Mabini is a coastal municipality in the province of Batangas in the Philippines, known for its diving spots and marine biodiversity.
-
E.
Vilaflor
Vilaflor is a high-altitude village on the island of Tenerife in Spain’s Canary Islands, known for its pine forests, traditional architecture, and proximity to Teide National Park.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9546fc620819093335988dbab3256 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6557e6d4c81909ed54a039e92a160 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.