Triple
T3112806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samar Island |
E64988
|
entity |
| Predicate | rankByAreaInPhilippines |
P46015
|
FINISHED |
| Object | third-largest island |
—
|
LITERAL 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: third-largest island | Statement: [Samar Island, rankByAreaInPhilippines, third-largest island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInPhilippines Context triple: [Samar Island, rankByAreaInPhilippines, third-largest island]
-
A.
rankByAreaInCanadaIslands
Indicates the numerical position of an island in Canada when all Canadian islands are ordered by their land area from largest to smallest.
-
B.
hasNumberOfBarangays
Indicates the total count of barangays associated with a given administrative unit or locality.
-
C.
areaRankInMalaysia
Indicates the relative position of an entity in a size-based ranking by area within Malaysia.
-
D.
populationRankInIndonesia
Indicates the relative position of an entity in terms of population size compared to other entities within Indonesia.
-
E.
populationRankInVietnam
Indicates the relative position of an entity in terms of population size compared to other entities within Vietnam.
- F. None of above. chosen
Provenance (4 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. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:04 p.m.