Triple
T16360733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norzagaray |
E397302
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Ipo Dam |
E942434
|
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: Ipo Dam | Statement: [Norzagaray, hasPart, Ipo Dam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ipo Dam Context triple: [Norzagaray, hasPart, Ipo Dam]
-
A.
Ipo Dam
chosen
Ipo Dam is a water reservoir and dam in Bulacan, Philippines, that forms a key part of the Angat–Ipo–La Mesa water system supplying Metro Manila.
-
B.
Mutirikwi Dam
Mutirikwi Dam is a major concrete arch dam in southeastern Zimbabwe that creates Lake Mutirikwi and serves as an important source of irrigation water and hydroelectric power.
-
C.
Guavio Dam
Guavio Dam is a major hydroelectric dam in Colombia known for its large reservoir and significant contribution to the country’s power generation.
-
D.
Tangga Dam
Tangga Dam is a hydroelectric power facility on Indonesia’s Asahan River that helps generate electricity by harnessing the river’s flow.
-
E.
Mula Dam
Mula Dam is a major irrigation and water-supply dam built on the Mula River in Maharashtra, India.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad304448190b3f6f0350a1e151d |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004575157c819098dbf27cf6641ff4 |
completed | May 10, 2026, 8:44 a.m. |
Created at: April 10, 2026, 5:08 a.m.