Triple
T7997746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Hierro |
E186168
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object | Malpaso |
E187542
|
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: Malpaso | Statement: [El Hierro, highestPoint, Malpaso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malpaso Context triple: [El Hierro, highestPoint, Malpaso]
-
A.
Malpaso
chosen
Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
-
B.
Plaridel
Plaridel is a municipality in the province of Bulacan in the Philippines, known for its historical significance and proximity to Metro Manila.
-
C.
Surigaonon
Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
-
D.
Bacolor
Bacolor is a historic municipality in the Philippine province of Pampanga, known for its cultural heritage and for being heavily affected by the 1991 Mount Pinatubo eruption.
-
E.
Carmona
Carmona is a municipality in the province of Cavite in the Philippines, known for its mix of residential communities and industrial estates.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c98e39081908904d36a31bd6768 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe10d5eb081909f257390094de442 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:17 p.m.