Triple
T8079385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurora |
E188575
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Dilasag
Dilasag is a coastal municipality in the Philippine province of Aurora known for its beaches, forests, and relatively remote, rural setting.
|
E710473
|
NE FINISHED |
How this triple was built (4 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: Dilasag | Statement: [Aurora, hasMunicipality, Dilasag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dilasag Context triple: [Aurora, hasMunicipality, Dilasag]
-
A.
Lalakay
Lalakay is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
-
B.
Balibago
Balibago is a bustling commercial and entertainment district in Angeles City, Pampanga, Philippines, known for its nightlife, shopping areas, and proximity to Clark Freeport Zone.
-
C.
Talugtug
Talugtug is a landlocked agricultural municipality in the province of Nueva Ecija in the Philippines.
-
D.
Kalamansig
Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
-
E.
Timugan
Timugan is a barangay (village-level administrative division) in the municipality of Los Baños in the province of Laguna, Philippines.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Dilasag Triple: [Aurora, hasMunicipality, Dilasag]
Generated description
Dilasag is a coastal municipality in the Philippine province of Aurora known for its beaches, forests, and relatively remote, rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dilasag Target entity description: Dilasag is a coastal municipality in the Philippine province of Aurora known for its beaches, forests, and relatively remote, rural setting.
-
A.
Lalakay
Lalakay is a barangay (village-level administrative division) within the municipality of Los Baños in the province of Laguna, Philippines.
-
B.
Balibago
Balibago is a bustling commercial and entertainment district in Angeles City, Pampanga, Philippines, known for its nightlife, shopping areas, and proximity to Clark Freeport Zone.
-
C.
Talugtug
Talugtug is a landlocked agricultural municipality in the province of Nueva Ecija in the Philippines.
-
D.
Kalamansig
Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
-
E.
Timugan
Timugan is a barangay (village-level administrative division) in the municipality of Los Baños in the province of Laguna, Philippines.
- F. None of above. chosen
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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a3f01c819096a2c9d5d5199fe6 |
completed | March 31, 2026, 3:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63f79ac08190af49e77bee67921d |
completed | April 1, 2026, 12:16 a.m. |
| NEDg | Description generation | batch_69cc651d340c819089306bac7110f57a |
completed | April 1, 2026, 12:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc666ecc04819092ee4cc035dde627 |
completed | April 1, 2026, 12:27 a.m. |
Created at: March 30, 2026, 5:28 p.m.