Triple
T12504749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagayan |
E298919
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Alcala
Alcala is a municipality in the province of Cagayan in the Philippines, known for its agricultural economy and rural communities.
|
E986705
|
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: Alcala | Statement: [Cagayan, hasCity, Alcala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alcala Context triple: [Cagayan, hasCity, Alcala]
-
A.
Alcalá de Henares
Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
-
B.
Alcalá la Real
Alcalá la Real is a historic town in southern Spain known for its imposing La Mota fortress and strategic location between Granada and Jaén.
-
C.
Salamanca
Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
-
D.
Salamanca
Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
-
E.
Salamanca
Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
- 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: Alcala Triple: [Cagayan, hasCity, Alcala]
Generated description
Alcala is a municipality in the province of Cagayan in the Philippines, known for its agricultural economy and rural communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alcala Target entity description: Alcala is a municipality in the province of Cagayan in the Philippines, known for its agricultural economy and rural communities.
-
A.
Alcalá de Henares
Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
-
B.
Alcalá la Real
Alcalá la Real is a historic town in southern Spain known for its imposing La Mota fortress and strategic location between Granada and Jaén.
-
C.
Salamanca
Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
-
D.
Salamanca
Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
-
E.
Salamanca
Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfddf38819099263b8b1e804736 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb5af708190b3786da334c3bf23 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce1b0ec8190bcbd245255e548b5 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64da735f48190b051ce173c13e5b2 |
completed | May 2, 2026, 7:16 p.m. |
Created at: April 8, 2026, 9:57 p.m.