Triple
T22502717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Grande de Mindanao |
E556314
|
entity |
| Predicate | rankByLengthInPhilippines |
P138579
|
FINISHED |
| Object | second longest river in the Philippines |
—
|
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: second longest river in the Philippines | Statement: [Rio Grande de Mindanao, rankByLengthInPhilippines, second longest river in the Philippines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByLengthInPhilippines Context triple: [Rio Grande de Mindanao, rankByLengthInPhilippines, second longest river in the Philippines]
-
A.
lengthRankingInPhilippines
chosen
Indicates the relative position of something in an ordered list based on its length specifically within the context of the Philippines.
-
B.
rankByAreaInPhilippines
Indicates the relative ordering of entities based on their area size specifically within the Philippines.
-
C.
rankByLengthInAsia
Indicates that entities are ordered or compared based on their length within the context of Asia.
-
D.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
-
E.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
- F. None of above.
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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5a01888190ba65a05616b63cbe |
completed | April 29, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.