Triple
T12478181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region I |
E298230
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Batac
Batac is a city in the Ilocos Region of the Philippines known for its historical significance and cultural heritage.
|
E987127
|
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: Batac | Statement: [Region I, hasCity, Batac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batac Context triple: [Region I, hasCity, Batac]
-
A.
Kabankalan
Kabankalan is a major inland city in the province of Negros Occidental in the Philippines, known as a commercial and agricultural hub in the southern part of the island.
-
B.
Balanga City
Balanga City is a component city in the province of Bataan, Philippines, known for its historical significance in World War II and its role as the provincial capital.
-
C.
Pagbilao
Pagbilao is a coastal municipality in the province of Quezon, Philippines, known for its power plant, beaches, and mangrove forests.
-
D.
Ilagan City
Ilagan City is a component city in the province of Isabela in the Philippines, known as an agricultural and commercial hub in the Cagayan Valley region.
-
E.
Dingalan
Dingalan is a coastal municipality in the province of Aurora, Philippines, known for its rugged mountains, scenic bays, and emerging eco-tourism attractions.
- 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: Batac Triple: [Region I, hasCity, Batac]
Generated description
Batac is a city in the Ilocos Region of the Philippines known for its historical significance and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Batac Target entity description: Batac is a city in the Ilocos Region of the Philippines known for its historical significance and cultural heritage.
-
A.
Kabankalan
Kabankalan is a major inland city in the province of Negros Occidental in the Philippines, known as a commercial and agricultural hub in the southern part of the island.
-
B.
Balanga City
Balanga City is a component city in the province of Bataan, Philippines, known for its historical significance in World War II and its role as the provincial capital.
-
C.
Pagbilao
Pagbilao is a coastal municipality in the province of Quezon, Philippines, known for its power plant, beaches, and mangrove forests.
-
D.
Ilagan City
Ilagan City is a component city in the province of Isabela in the Philippines, known as an agricultural and commercial hub in the Cagayan Valley region.
-
E.
Dingalan
Dingalan is a coastal municipality in the province of Aurora, Philippines, known for its rugged mountains, scenic bays, and emerging eco-tourism attractions.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dcc24e48190ae9c367a03f659f4 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64ba5efc881909784037b95f7bbe3 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce0ca288190bbbcb5459f914c19 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64df6488481909dea8387e7000d15 |
completed | May 2, 2026, 7:18 p.m. |
Created at: April 8, 2026, 9:56 p.m.