Triple
T37744335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angat Dam |
E940804
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Angat–Umiray–Ipo water system
The Angat–Umiray–Ipo water system is a major integrated water supply and hydroelectric complex in the Philippines that channels and stores water from multiple sources to provide most of Metro Manila’s potable water and power generation needs.
|
E2240978
|
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: Angat–Umiray–Ipo water system | Statement: [Angat Dam, partOf, Angat–Umiray–Ipo water system]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Angat–Umiray–Ipo water system Triple: [Angat Dam, partOf, Angat–Umiray–Ipo water system]
Generated description
The Angat–Umiray–Ipo water system is a major integrated water supply and hydroelectric complex in the Philippines that channels and stores water from multiple sources to provide most of Metro Manila’s potable water and power generation needs.
Provenance (5 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_69f76ee0e32c8190b40a3b4cf590337c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaec146a4819096a7cf40618a95e4 |
completed | May 6, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40d68dcba4819082b32fa5159797cd |
completed | June 28, 2026, 8:08 a.m. |
| NEDg | Description generation | batch_6a40d87bd2108190b90b05fe3b93cbec |
completed | June 28, 2026, 8:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40d9f174f481909c3c8adbe39ac518 |
completed | June 28, 2026, 8:23 a.m. |
Created at: May 3, 2026, 4:19 p.m.