Triple
T3112798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samar Island |
E64988
|
entity |
| Predicate | hasProvince |
P285
|
FINISHED |
| Object | Samar |
E66623
|
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: Samar | Statement: [Samar Island, hasProvince, Samar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samar Context triple: [Samar Island, hasProvince, Samar]
-
A.
Samar
Samar is a surname most notably associated with Sima Samar, an Afghan human rights advocate, physician, and former minister.
-
B.
Samar Island
Samar Island is a large island in the Eastern Visayas region of the Philippines, known for its rugged terrain, rich biodiversity, and distinct local culture.
-
C.
Pomorye
Pomorye is a historical coastal region of northern Russia along the White Sea, traditionally inhabited by the Pomors and known for maritime trade and exploration.
-
D.
Samar Province
chosen
Samar Province is a largely rural island province in the Eastern Visayas region of the Philippines, known for its rugged landscapes, caves, and strong Waray-speaking cultural heritage.
-
E.
Leyte
Leyte is a large island province in the Eastern Visayas region of the Philippines, known for its rich cultural traditions and historical significance, including major World War II events.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43c79448190aa72f707319e8c5e |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b367e5581081908c44bc8d9492c936 |
completed | March 13, 2026, 1:27 a.m. |
Created at: March 8, 2026, 3:04 p.m.