Triple
T4719348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taguig |
E104725
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
San Miguel
San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
|
E465743
|
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: San Miguel | Statement: [Taguig, hasBarangay, San Miguel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Miguel Context triple: [Taguig, hasBarangay, San Miguel]
-
A.
San Miguel
San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
-
B.
San Miguel
San Miguel is an active stratovolcano in eastern El Salvador, known for its frequent eruptions and prominent conical shape within the Central American volcanic chain.
-
C.
San Miguel
San Miguel is a town located within Bolívar Province in central Ecuador, known for its Andean setting and local agricultural activities.
-
D.
San Miguel
San Miguel is a coastal district of Lima, Peru, known for its residential areas, shopping centers, and access to major avenues and the Pacific shoreline.
-
E.
Piñas
Piñas is a barrio (neighborhood or district) within the municipality of Dorado in Puerto Rico.
- 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: San Miguel Triple: [Taguig, hasBarangay, San Miguel]
Generated description
San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Miguel Target entity description: San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
-
A.
San Miguel
San Miguel is an active stratovolcano in eastern El Salvador, known for its frequent eruptions and prominent conical shape within the Central American volcanic chain.
-
B.
San Miguel
San Miguel is a town located within Bolívar Province in central Ecuador, known for its Andean setting and local agricultural activities.
-
C.
San Miguel
San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
-
D.
San Miguel
San Miguel is a coastal district of Lima, Peru, known for its residential areas, shopping centers, and access to major avenues and the Pacific shoreline.
-
E.
Piñas
Piñas is a barrio (neighborhood or district) within the municipality of Dorado in Puerto Rico.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd642779a08190b01e588d515cf498 |
completed | March 20, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be108bc0048190aeea8674f75105e5 |
completed | March 21, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_69be2e247f28819099e14db2c551a8f2 |
completed | March 21, 2026, 5:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be2ee962f88190927ccb32acdcc2e8 |
completed | March 21, 2026, 5:38 a.m. |
Created at: March 20, 2026, 1:18 p.m.